scholarly journals Laminar dependence of neuronal correlations in visual cortex

2013 ◽  
Vol 109 (4) ◽  
pp. 940-947 ◽  
Author(s):  
Matthew A. Smith ◽  
Xiaoxuan Jia ◽  
Amin Zandvakili ◽  
Adam Kohn
Keyword(s):  
Visual Cortex ◽  
Field Potential ◽  
Low Frequency ◽  
Population Coding ◽  
Neuronal Responses ◽  
Cortical Function ◽  
Area V2 ◽  
Complementary Pattern ◽  
Deep Layers ◽  
Slow Timescale

Neuronal responses are correlated on a range of timescales. Correlations can affect population coding and may play an important role in cortical function. Correlations are known to depend on stimulus drive, behavioral context, and experience, but the mechanisms that determine their properties are poorly understood. Here we make use of the laminar organization of cortex, with its variations in sources of input, local circuit architecture, and neuronal properties, to test whether networks engaged in similar functions but with distinct properties generate different patterns of correlation. We find that slow timescale correlations are prominent in the superficial and deep layers of primary visual cortex (V1) of macaque monkeys, but near zero in the middle layers. Brief timescale correlation (synchrony), on the other hand, was slightly stronger in the middle layers of V1, although evident at most cortical depths. Laminar variations were also apparent in the power of the local field potential, with a complementary pattern for low frequency (<10 Hz) and gamma (30–50 Hz) power. Recordings in area V2 revealed a laminar dependence similar to V1 for synchrony, but slow timescale correlations were not different between the input layers and nearby locations. Our results reveal that cortical circuits in different laminae can generate remarkably different patterns of correlations, despite being tightly interconnected.

scholarly journals Visual recognition is heralded by shifts in local field potential oscillations and inhibitory networks in primary visual cortex

2020 ◽  
Author(s):  
Dustin J. Hayden ◽  
Daniel P. Montgomery ◽  
Samuel F. Cooke ◽  
Mark F. Bear
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Local Field ◽  
High Frequency ◽  
Peak Power ◽  
Field Potential ◽  
Low Frequency ◽  
Inhibitory Neurons ◽  
Stimulus Familiarity ◽  
Frequency Power

AbstractFiltering out familiar, irrelevant stimuli eases the computational burden on the cerebral cortex. Inhibition is a candidate mechanism in this filtration process. Oscillations in the cortical local field potential (LFP) serve as markers of the engagement of different inhibitory neurons. In awake mice, we find pronounced changes in LFP oscillatory activity present in layer 4 of primary visual cortex (V1) with progressive stimulus familiarity. Over days of repeated stimulus presentation, low frequency (alpha/beta ~15 Hz peak) power increases while high frequency (gamma ~65 Hz peak) power decreases. This high frequency activity re-emerges when a novel stimulus is shown. Thus, high frequency power is a marker of novelty while low frequency power signifies familiarity. Two-photon imaging of neuronal activity reveals that parvalbumin-expressing inhibitory neurons disengage with familiar stimuli and reactivate to novelty, consistent with their known role in gamma oscillations, whereas somatostatin-expressing inhibitory neurons show opposing activity patterns, indicating a contribution to the emergence of lower frequency oscillations. We also reveal that stimulus familiarity and novelty have differential effects on oscillations and cell activity over a shorter timescale of seconds. Taken together with previous findings, we propose a model in which two interneuron circuits compete to drive familiarity or novelty encoding.

scholarly journals Subcortical theta oscillations alternate with high amplitude neocortical population within synchronized states

2018 ◽  
Author(s):  
Erin Munro Krull ◽  
Shuzo Sakata ◽  
Taro Toyoizumi
Keyword(s):  
Slow Wave Sleep ◽  
Field Potential ◽  
Low Frequency ◽  
Cortical Activity ◽  
High Amplitude ◽  
Theta Oscillations ◽  
Theta Frequency ◽  
Deep Layers ◽  
Two Populations ◽  
Delta Oscillations

AbstractSynchronized states are marked by large-amplitude low-frequency oscillations in the cortex. These states can be seen during quiet waking or slow-wave sleep. Within synchronized states, previous studies have noted a plethora of different types of activity, including delta oscillations (0.5-4 Hz) and slow oscillations (<1 Hz) in the cortex and large- and small-irregular activity in the hippocampus. However, it is not still fully characterized how neural populations contribute to the synchronized state. Here we apply independent component analysis (ICA) to parse which populations are involved in different kinds of cortical activity, and find two populations that alternate throughout synchronized states. One population broadly affects cortical deep layers, and is associated with larger amplitude slower cortical activity. The other population exhibits theta-frequency oscillations that are not easily observed in raw field potential recordings. These theta oscillations apparently come from below the cortex, suggesting hippocampal origin, and are associated with smaller amplitude faster cortical activity. Relative involvement of these two alternating populations may indicate different modes of operation within synchronized states.

scholarly journals Uncoupling PSD-95 Interactions Leads to Rapid Recovery of Cortical Function after Focal Stroke

2013 ◽  
Vol 33 (12) ◽  
pp. 1937-1943 ◽  
Author(s):  
Luka R Srejic ◽  
William D Hutchison ◽  
Michelle M Aarts
Keyword(s):  
Microelectrode Array ◽  
Brain Activity ◽  
Field Potential ◽  
Field Potentials ◽  
Behavioral Models ◽  
Cortical Function ◽  
Evoked Field Potentials ◽  
Deep Layers ◽  
Eeg Power

Since the most significant ischemic sequelae occur within hours of stroke, it is necessary to understand how neuronal function changes during this time. While histologic and behavioral models show the extent of stroke-related damage, only in vivo recordings can illustrate changes in brain activity during stroke and validate effectiveness of neuroprotective compounds. Spontaneous and evoked field potentials (fEPs) were recorded in the deep layers of the cortex with a linear microelectrode array for 3 hours after focal stroke in anesthetized rats. Tat-NR2B9c peptide, which confers neuroprotection by uncoupling the PSD-95 protein from N-methyl-D-aspartate receptor (NMDAR), was administered 5 minutes before ischemia. Evoked field potentials were completely suppressed within 3 minutes of infarct in all ischemic groups. Evoked field potential recovery after stroke in rats treated with Tat-NR2B9c (83% of baseline) was greater compared with stroke-only (61% of baseline) or control peptide (Tat-NR2B-AA; 67% of baseline) groups ( P<0.001). Electroencephalography (EEG) power was higher in Tat-NR2B9c-treated animals at both 20 minutes and 1 hour (50% and 73% of baseline, respectively) compared with stroke-only and Tat-NR2B-AA-treated rats ( P<0.05). Tat-NR2B9c significantly reduces stroke-related cortical dysfunction as evidenced by greater recovery of fEPs and EEG power; illustrating the immediate effects of the compound on poststroke brain function.

scholarly journals Solving visual correspondence between the two eyes via domain-based population encoding in nonhuman primates

2017 ◽  
Vol 114 (49) ◽  
pp. 13024-13029 ◽  
Author(s):  
Gang Chen ◽  
Haidong D. Lu ◽  
Hisashi Tanigawa ◽  
Anna W. Roe
Keyword(s):  
Visual Cortex ◽  
Nonhuman Primates ◽  
Population Coding ◽  
Stereoscopic Vision ◽  
Imaging Data ◽  
Area V2 ◽  
Visual Correspondence ◽  
Visual Cortical Area ◽  
Visual Cortical ◽  
The Brain

Stereoscopic vision depends on correct matching of corresponding features between the two eyes. It is unclear where the brain solves this binocular correspondence problem. Although our visual system is able to make correct global matches, there are many possible false matches between any two images. Here, we use optical imaging data of binocular disparity response in the visual cortex of awake and anesthetized monkeys to demonstrate that the second visual cortical area (V2) is the first cortical stage that correctly discards false matches and robustly encodes correct matches. Our findings indicate that a key transformation for achieving depth perception lies in early stages of extrastriate visual cortex and is achieved by population coding.

scholarly journals Lateral phase differences in a population model of the visual cortex are sufficient for the development of rhythmic spatial sampling

2020 ◽  
Author(s):  
Justin D. Yi ◽  
Katsushi Arisaka
Keyword(s):  
Visual Cortex ◽  
Spatial Attention ◽  
Phase Difference ◽  
Computational Study ◽  
Field Potential ◽  
Low Frequency ◽  
Probability Of Detection ◽  
Population Activity ◽  
Attention Task ◽  
Phase Differences

AbstractWhen attending to many spatially distributed visual stimuli, attention is reweighted rhythmically at 4-8 Hz. The probability of detection depends on the phase at which a stimulus is deployed relative to this intrinsic rhythm. The reweighting oscillations can be observed both electrophysiologically and behaviorally, and appear to be regulated by the pulvinar. Based on these findings, we considered the computational consequences of allowing feedback to shape the distribution of inhibitory oscillations from the thalamus, as measured by a local field potential (LFP) phases in the 8 Hz low alpha-band, across laterally-connected regions of the visual cortex. We constructed a population activity model with lateral and feedforward connections. In agreement with prior models, we found that the sign of the lateral phase difference in the inhibitory low-frequency oscillations regulated the direction of communication between the laterally-connected regions. Furthermore, the phase difference induced periodicity in the dynamics of a downstream winner-takes-all attractor network such that periodic switching between states was observed. We finally simulated a simple spatial attention task. We found rhythmic 8 Hz sampling between two regions when a lateral phase difference was present—an effect that disappeared when the lateral phase difference was zero. These findings are in agreement with spatial attention literature and suggest that lateral phase differences are essential for manifesting communicational asymmetries in laterally-connected visual cortices. Our model predicts that population-specific phase differences are critical for sampling the spatial extent of stimuli.Author summaryWe conducted a computational study of the effects of lateral phase differences in a simulated model of the visual cortex. Lateral phase differences are defined to be when the phase of an intrinsic low-frequency inhibitory oscillation varies consistently across populations in the same cortical area. For example, our model was intended to capture the dynamics of a retinotopic cortex where feedback from the frotoparietal areas via the pulvinar nucleus assigned laterally-connected regions of the visual cortex different phases. We found that the sign of the phase differences influenced the direction of lateral communication. Furthermore, the phase differences introduced rhythmicity in the downstream areas, thus allowing us to simulate rhythmic spatial selection of stimuli. Prior to the current study, the influence of inter-areal phase differences in feedforward models had been well characterized. Our model provides new insights into the dynamics of population-specific lateral phase differences and predicts that the development of phase differences across the visual cortex are critical for the allocation of attention in space.

scholarly journals Myelin densities in retinotopically defined dorsal visual areas of the macaque

2021 ◽  
Author(s):  
Xiaolian Li ◽  
Qi Zhu ◽  
Wim Vanduffel
Keyword(s):  
Visual Cortex ◽  
Visual Field ◽  
Cortical Thickness ◽  
New World Monkeys ◽  
Isotropic Resolution ◽  
Density Mapping ◽  
Area V2 ◽  
Visual Areas ◽  
Density Results

AbstractThe visuotopic organization of dorsal visual cortex rostral to area V2 in primates has been a longstanding source of controversy. Using sub-millimeter phase-encoded retinotopic fMRI mapping, we recently provided evidence for a surprisingly similar visuotopic organization in dorsal visual cortex of macaques compared to previously published maps in New world monkeys (Zhu and Vanduffel, Proc Natl Acad Sci USA 116:2306–2311, 2019). Although individual quadrant representations could be robustly delineated in that study, their grouping into hemifield representations remains a major challenge. Here, we combined in-vivo high-resolution myelin density mapping based on MR imaging (400 µm isotropic resolution) with fine-grained retinotopic fMRI to quantitatively compare myelin densities across retinotopically defined visual areas in macaques. Complementing previously documented differences in populational receptive-field (pRF) size and visual field signs, myelin densities of both quadrants of the dorsolateral posterior area (DLP) and area V3A are significantly different compared to dorsal and ventral area V3. Moreover, no differences in myelin density were observed between the two matching quadrants belonging to areas DLP, V3A, V1, V2 and V4, respectively. This was not the case, however, for the dorsal and ventral quadrants of area V3, which showed significant differences in MR-defined myelin densities, corroborating evidence of previous myelin staining studies. Interestingly, the pRF sizes and visual field signs of both quadrant representations in V3 are not different. Although myelin density correlates with curvature and anticorrelates with cortical thickness when measured across the entire cortex, exactly as in humans, the myelin density results in the visual areas cannot be explained by variability in cortical thickness and curvature between these areas. The present myelin density results largely support our previous model to group the two quadrants of DLP and V3A, rather than grouping DLP- with V3v into a single area VLP, or V3d with V3A+ into DM.

scholarly journals Integral Equations for Problems on Wave Propagation in Near-Earth Plasma

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1395
Author(s):  
Danila Kostarev ◽  
Dmitri Klimushkin ◽  
Pavel Mager
Keyword(s):  
Magnetic Field ◽  
Integral Equations ◽  
Field Potential ◽  
Low Frequency ◽  
Fredholm Equation ◽  
Compression Waves ◽  
Parallel Component ◽  
Electric Field Potential ◽  
The Magnetic Field ◽  
Low Frequency Waves

We consider the solutions of two integrodifferential equations in this work. These equations describe the ultra-low frequency waves in the dipol-like model of the magnetosphere in the gyrokinetic framework. The first one is reduced to the homogeneous, second kind Fredholm equation. This equation describes the structure of the parallel component of the magnetic field of drift-compression waves along the Earth’s magnetic field. The second equation is reduced to the inhomogeneous, second kind Fredholm equation. This equation describes the field-aligned structure of the parallel electric field potential of Alfvén waves. Both integral equations are solved numerically.

scholarly journals Superimposed gratings induce diverse response patterns of gamma oscillations in primary visual cortex

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bin Wang ◽  
Chuanliang Han ◽  
Tian Wang ◽  
Weifeng Dai ◽  
Yang Li ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Field Potential ◽  
Gamma Oscillations ◽  
Neural Mechanisms ◽  
Model Parameters ◽  
Response Patterns ◽  
Region Difference ◽  
High Gamma ◽  
Spiking Activity

AbstractStimulus-dependence of gamma oscillations (GAMMA, 30–90 Hz) has not been fully understood, but it is important for revealing neural mechanisms and functions of GAMMA. Here, we recorded spiking activity (MUA) and the local field potential (LFP), driven by a variety of plaids (generated by two superimposed gratings orthogonal to each other and with different contrast combinations), in the primary visual cortex of anesthetized cats. We found two distinct narrow-band GAMMAs in the LFPs and a variety of response patterns to plaids. Similar to MUA, most response patterns showed that the second grating suppressed GAMMAs driven by the first one. However, there is only a weak site-by-site correlation between cross-orientation interactions in GAMMAs and those in MUAs. We developed a normalization model that could unify the response patterns of both GAMMAs and MUAs. Interestingly, compared with MUAs, the GAMMAs demonstrated a wider range of model parameters and more diverse response patterns to plaids. Further analysis revealed that normalization parameters for high GAMMA, but not those for low GAMMA, were significantly correlated with the discrepancy of spatial frequency between stimulus and sites’ preferences. Consistent with these findings, normalization parameters and diversity of high GAMMA exhibited a clear transition trend and region difference between area 17 to 18. Our results show that GAMMAs are also regulated in the form of normalization, but that the neural mechanisms for these normalizations might differ from those of spiking activity. Normalizations in different brain signals could be due to interactions of excitation and inhibitions at multiple stages in the visual system.

scholarly journals A direct interareal feedback-to-feedforward circuit in primate visual cortex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Caitlin Siu ◽  
Justin Balsor ◽  
Sam Merlin ◽  
Frederick Federer ◽  
Alessandra Angelucci
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Projection Neurons ◽  
V1 Neurons ◽  
Cortical Areas ◽  
Area V2 ◽  
Computational Work ◽  
Primate Visual Cortex ◽  
Similar Area ◽  
Hierarchical Computation

AbstractThe mammalian sensory neocortex consists of hierarchically organized areas reciprocally connected via feedforward (FF) and feedback (FB) circuits. Several theories of hierarchical computation ascribe the bulk of the computational work of the cortex to looped FF-FB circuits between pairs of cortical areas. However, whether such corticocortical loops exist remains unclear. In higher mammals, individual FF-projection neurons send afferents almost exclusively to a single higher-level area. However, it is unclear whether FB-projection neurons show similar area-specificity, and whether they influence FF-projection neurons directly or indirectly. Using viral-mediated monosynaptic circuit tracing in macaque primary visual cortex (V1), we show that V1 neurons sending FF projections to area V2 receive monosynaptic FB inputs from V2, but not other V1-projecting areas. We also find monosynaptic FB-to-FB neuron contacts as a second motif of FB connectivity. Our results support the existence of FF-FB loops in primate cortex, and suggest that FB can rapidly and selectively influence the activity of incoming FF signals.

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