scholarly journals Demands of visual processing hierarchy shape laminar compartmentalization of attention modulation of luminance contrast in area V4

2021 ◽  
Author(s):  
Xiang Wang ◽  
Anirvan S. Nandy ◽  
Monika P. Jadi
Keyword(s):  
Visual Processing ◽  
Luminance Contrast ◽  
Cortical Layer ◽  
Inhibitory Neurons ◽  
Spatial Integration ◽  
Low Contrast ◽  
Area V4 ◽  
Visual Areas ◽  
Excitatory Neurons ◽  
Contrast Information

ABSTRACTContrast is a key feature of the visual scene that aids object recognition. Attention has been shown to selectively enhance the responses to low contrast stimuli in visual area V4, a critical hub that sends projections both up and down the visual hierarchy. Veridical encoding of contrast information is a key computation in early visual areas, while later stages encode higher level features that benefit from improved sensitivity to low contrast. How area V4 meets these distinct information processing demands in the attentive state is not known. We found that attentional modulation of contrast responses in area V4 is cortical layer and cell-class specific. Putative excitatory neurons in the superficial output layers that project to higher areas show enhanced boosting of low contrast information. On the other hand, putative excitatory neurons of deep output layers that project to early visual areas exhibit contrast-independent scaling. Computational modeling revealed that such layer-wise differences may result from variations in spatial integration extent of inhibitory neurons. These findings reveal that the nature of interactions between attention and contrast in V4 is highly compartmentalized, in alignment with the demands of the visual processing hierarchy.

scholarly journals Brain state and cortical layer-specific mechanisms underlying perception at threshold

2021 ◽  
Author(s):  
Mitchell P Morton ◽  
Sachira Denagamage ◽  
Isabel J Blume ◽  
John H Reynolds ◽  
Monika P Jadi ◽  
...  
Keyword(s):  
Cortical Layer ◽  
Inhibitory Neurons ◽  
Brain State ◽  
Cortical Layers ◽  
Attention Task ◽  
Sensory Stimuli ◽  
Area V4 ◽  
Perceptual Stability ◽  
Deep Layers ◽  
Perceptual Threshold

Identical stimuli can be perceived or go unnoticed across successive presentations, producing divergent behavioral readouts despite similarities in sensory input. We hypothesized that fluctuations in neurophysiological states in the sensory neocortex, which could alter cortical processing at the level of neural subpopulations, underlies this perceptual variability. We analyzed cortical layer-specific electrophysiological activity in visual area V4 during a cued attention task. We find that hit trials are characterized by a larger pupil diameter and lower incidence of microsaccades, indicative of a behavioral state with increased arousal and perceptual stability. Target stimuli presented at perceptual threshold evoke elevated multi-unit activity in V4 neurons in hit trials compared to miss trials, across all cortical layers. Putative excitatory and inhibitory neurons are strongly positively modulated in the input (IV) and deep (V & VI) layers of the cortex during hit trials. Excitatory neurons in the superficial cortical layers exhibit lower variability in hit trials. Deep layer neurons are less phase-locked to low frequency rhythms in hits. Hits are also characterized by greater interlaminar coherence between the superficial and deep layers in the pre-stimulus period, and a complementary pattern between the input layer and both the superficial and deep layers in the stimulus-evoked period. Taken together, these results indicate that a state of elevated levels of arousal and perceptual stability allow enhanced processing of sensory stimuli, which contributes to hits at perceptual threshold.

scholarly journals Stimulus selectivity and response latency in putative inhibitory and excitatory neurons of the primate inferior temporal cortex

2012 ◽  
Vol 108 (10) ◽  
pp. 2725-2736 ◽  
Author(s):  
Ryan E. B. Mruczek ◽  
David L. Sheinberg
Keyword(s):  
Functional Properties ◽  
Response Latency ◽  
Visual Processing ◽  
Temporal Cortex ◽  
Cell Types ◽  
Inferior Temporal Cortex ◽  
Inhibitory Neurons ◽  
Response Latencies ◽  
Firing Rates ◽  
Excitatory Neurons

The cerebral cortex is composed of many distinct classes of neurons. Numerous studies have demonstrated corresponding differences in neuronal properties across cell types, but these comparisons have largely been limited to conditions outside of awake, behaving animals. Thus the functional role of the various cell types is not well understood. Here, we investigate differences in the functional properties of two widespread and broad classes of cells in inferior temporal cortex of macaque monkeys: inhibitory interneurons and excitatory projection cells. Cells were classified as putative inhibitory or putative excitatory neurons on the basis of their extracellular waveform characteristics (e.g., spike duration). Consistent with previous intracellular recordings in cortical slices, putative inhibitory neurons had higher spontaneous firing rates and higher stimulus-evoked firing rates than putative excitatory neurons. Additionally, putative excitatory neurons were more susceptible to spike waveform adaptation following very short interspike intervals. Finally, we compared two functional properties of each neuron's stimulus-evoked response: stimulus selectivity and response latency. First, putative excitatory neurons showed stronger stimulus selectivity compared with putative inhibitory neurons. Second, putative inhibitory neurons had shorter response latencies compared with putative excitatory neurons. Selectivity differences were maintained and latency differences were enhanced during a visual search task emulating more natural viewing conditions. Our results suggest that short-latency inhibitory responses are likely to sculpt visual processing in excitatory neurons, yielding a sparser visual representation.

scholarly journals Temporally evolving gain mechanisms of attention in macaque area V4

2017 ◽  
Vol 118 (2) ◽  
pp. 964-985 ◽  
Author(s):  
Ilaria Sani ◽  
Elisa Santandrea ◽  
Maria Concetta Morrone ◽  
Leonardo Chelazzi
Keyword(s):  
Visual Processing ◽  
Temporal Dynamics ◽  
Luminance Contrast ◽  
Response Functions ◽  
Fundamental Factor ◽  
Area V4 ◽  
V4 Neurons ◽  
Contrast Response

We offer an innovative perspective on the interplay between attention and luminance contrast in macaque area V4, one in which time becomes a fundamental factor. We place emphasis on the temporal dynamics of attentional effects, pioneering the notion that attention modulates contrast response functions of V4 neurons via the sequential engagement of distinct gain mechanisms. These findings advance understanding of attentional influences on visual processing and help reconcile divergent results in the literature.

scholarly journals How attention extracts objects from noise

2013 ◽  
Vol 110 (6) ◽  
pp. 1346-1356 ◽  
Author(s):  
Michael S. Pratte ◽  
Sam Ling ◽  
Jascha D. Swisher ◽  
Frank Tong
Keyword(s):  
Visual Processing ◽  
Activity Patterns ◽  
Occipital Cortex ◽  
Relevant Information ◽  
Visual Input ◽  
Visual Noise ◽  
Noise Filtering ◽  
Area V4 ◽  
Face Area ◽  
Visual Areas

The visual system is remarkably proficient at extracting relevant object information from noisy, cluttered environments. Although attention is known to enhance sensory processing, the mechanisms by which attention extracts relevant information from noise are not well understood. According to the perceptual template model, attention may act to amplify responses to all visual input, or it may act as a noise filter, dampening responses to irrelevant visual noise. Amplification allows for improved performance in the absence of visual noise, whereas a noise-filtering mechanism can only improve performance if the target stimulus appears in noise. Here, we used fMRI to investigate how attention modulates cortical responses to objects at multiple levels of the visual pathway. Participants viewed images of faces, houses, chairs, and shoes, presented in various levels of visual noise. We used multivoxel pattern analysis to predict the viewed object category, for attended and unattended stimuli, from cortical activity patterns in individual visual areas. Early visual areas, V1 and V2, exhibited a benefit of attention only at high levels of visual noise, suggesting that attention operates via a noise-filtering mechanism at these early sites. By contrast, attention led to enhanced processing of noise-free images (i.e., amplification) only in higher visual areas, including area V4, fusiform face area, mid-Fusiform area, and the lateral occipital cortex. Together, these results suggest that attention improves people's ability to discriminate objects by de-noising visual input in early visual areas and amplifying this noise-reduced signal at higher stages of visual processing.

scholarly journals Dynamics of excitatory and inhibitory networks are differentially altered by selective attention

2016 ◽  
Vol 116 (4) ◽  
pp. 1807-1820 ◽  
Author(s):  
Adam C. Snyder ◽  
Michael J. Morais ◽  
Matthew A. Smith
Keyword(s):  
Time Course ◽  
Rhesus Macaques ◽  
Inhibitory Neurons ◽  
Waveform Analysis ◽  
Extrastriate Cortex ◽  
Behavioral Measure ◽  
Area V4 ◽  
Excitatory Neurons ◽  
Time Course Of Attention

Inhibition and excitation form two fundamental modes of neuronal interaction, yet we understand relatively little about their distinct roles in service of perceptual and cognitive processes. We developed a multidimensional waveform analysis to identify fast-spiking (putative inhibitory) and regular-spiking (putative excitatory) neurons in vivo and used this method to analyze how attention affects these two cell classes in visual area V4 of the extrastriate cortex of rhesus macaques. We found that putative inhibitory neurons had both greater increases in firing rate and decreases in correlated variability with attention compared with putative excitatory neurons. Moreover, the time course of attention effects for putative inhibitory neurons more closely tracked the temporal statistics of target probability in our task. Finally, the session-to-session variability in a behavioral measure of attention covaried with the magnitude of this effect. Together, these results suggest that selective targeting of inhibitory neurons and networks is a critical mechanism for attentional modulation.

scholarly journals Neuron-specific spinal cord translatomes reveal a neuropeptide code for mouse dorsal horn excitatory neurons

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rebecca Rani Das Gupta ◽  
Louis Scheurer ◽  
Pawel Pelczar ◽  
Hendrik Wildner ◽  
Hanns Ulrich Zeilhofer
Keyword(s):  
Spinal Cord ◽  
Dorsal Horn ◽  
Functional Organization ◽  
Affinity Purification ◽  
Expression Patterns ◽  
Inhibitory Neurons ◽  
Dorsal Horn Neurons ◽  
Expression Of Genes ◽  
Excitatory Neurons ◽  
Genes Encoding

AbstractThe spinal dorsal horn harbors a sophisticated and heterogeneous network of excitatory and inhibitory neurons that process peripheral signals encoding different sensory modalities. Although it has long been recognized that this network is crucial both for the separation and the integration of sensory signals of different modalities, a systematic unbiased approach to the use of specific neuromodulatory systems is still missing. Here, we have used the translating ribosome affinity purification (TRAP) technique to map the translatomes of excitatory glutamatergic (vGluT2+) and inhibitory GABA and/or glycinergic (vGAT+ or Gad67+) neurons of the mouse spinal cord. Our analyses demonstrate that inhibitory and excitatory neurons are not only set apart, as expected, by the expression of genes related to the production, release or re-uptake of their principal neurotransmitters and by genes encoding for transcription factors, but also by a differential engagement of neuromodulator, especially neuropeptide, signaling pathways. Subsequent multiplex in situ hybridization revealed eleven neuropeptide genes that are strongly enriched in excitatory dorsal horn neurons and display largely non-overlapping expression patterns closely adhering to the laminar and presumably also functional organization of the spinal cord grey matter.

scholarly journals Adaptive Integration in the Visual Cortex by Depressing Recurrent Cortical Circuits

2008 ◽  
Vol 20 (7) ◽  
pp. 1847-1872 ◽  
Author(s):  
Mark C. W. van Rossum ◽  
Matthijs A. A. van der Meer ◽  
Dengke Xiao ◽  
Mike W. Oram
Keyword(s):  
Visual Cortex ◽  
Physiological Data ◽  
High Contrast ◽  
Cortical Circuits ◽  
Response Latencies ◽  
Low Contrast ◽  
Visual Areas ◽  
Higher Visual Areas ◽  
Recurrent Connections

Neurons in the visual cortex receive a large amount of input from recurrent connections, yet the functional role of these connections remains unclear. Here we explore networks with strong recurrence in a computational model and show that short-term depression of the synapses in the recurrent loops implements an adaptive filter. This allows the visual system to respond reliably to deteriorated stimuli yet quickly to high-quality stimuli. For low-contrast stimuli, the model predicts long response latencies, whereas latencies are short for high-contrast stimuli. This is consistent with physiological data showing that in higher visual areas, latencies can increase more than 100 ms at low contrast compared to high contrast. Moreover, when presented with briefly flashed stimuli, the model predicts stereotypical responses that outlast the stimulus, again consistent with physiological findings. The adaptive properties of the model suggest that the abundant recurrent connections found in visual cortex serve to adapt the network's time constant in accordance with the stimulus and normalizes neuronal signals such that processing is as fast as possible while maintaining reliability.

scholarly journals Mechanisms underlying contrast-dependent orientation selectivity in mouse V1

2018 ◽  
Vol 115 (45) ◽  
pp. 11619-11624 ◽  
Author(s):  
Wei P. Dai ◽  
Douglas Zhou ◽  
David W. McLaughlin ◽  
David Cai
Keyword(s):  
Large Scale ◽  
Feedback Inhibition ◽  
Orientation Selectivity ◽  
Inhibitory Neurons ◽  
Orientation Tuning ◽  
Response Properties ◽  
Firing Rates ◽  
Excitatory Neurons ◽  
Cortical Excitation ◽  
Contrast Invariance

Recent experiments have shown that mouse primary visual cortex (V1) is very different from that of cat or monkey, including response properties—one of which is that contrast invariance in the orientation selectivity (OS) of the neurons’ firing rates is replaced in mouse with contrast-dependent sharpening (broadening) of OS in excitatory (inhibitory) neurons. These differences indicate a different circuit design for mouse V1 than that of cat or monkey. Here we develop a large-scale computational model of an effective input layer of mouse V1. Constrained by experiment data, the model successfully reproduces experimentally observed response properties—for example, distributions of firing rates, orientation tuning widths, and response modulations of simple and complex neurons, including the contrast dependence of orientation tuning curves. Analysis of the model shows that strong feedback inhibition and strong orientation-preferential cortical excitation to the excitatory population are the predominant mechanisms underlying the contrast-sharpening of OS in excitatory neurons, while the contrast-broadening of OS in inhibitory neurons results from a strong but nonpreferential cortical excitation to these inhibitory neurons, with the resulting contrast-broadened inhibition producing a secondary enhancement on the contrast-sharpened OS of excitatory neurons. Finally, based on these mechanisms, we show that adjusting the detailed balances between the predominant mechanisms can lead to contrast invariance—providing insights for future studies on contrast dependence (invariance).

Spatial frequency analsis in early visual processing

1980 ◽  
Vol 290 (1038) ◽  
pp. 11-22 ◽  
Keyword(s):  
Spatial Frequency ◽  
Visual Processing ◽  
Spatial Information ◽  
Multiple Channels ◽  
Low Contrast ◽  
Local Sign ◽  
Early Visual Processing ◽  
Low Luminance ◽  
Lowered Sensitivity ◽  
Prior Adaptation

The existence of multiple channels, or multiple receptive field sizes, in the visual system does not commit us to any particular theory of spatial encoding in vision. However, distortions of apparent spatial frequency and width in a wide variety of conditions favour the idea that each channel carries a width- or frequency-related code or ‘label’ rather than a ‘local sign’ or positional label. When distortions of spatial frequency occur without prior adaptation (e.g. at low contrast or low luminance) they are associated with lowered sensitivity, and may be due to a mismatch between the perceptual labels and the actual tuning of the channels. A low-level representation of retinal space could be constructed from the spatial information encoded by the channels, rather than being projected intact from the retina.

scholarly journals Single-cell transcriptomic analysis identifies neocortical developmental differences between human and mouse

2020 ◽  
Author(s):  
Ziheng Zhou ◽  
Shuguang Wang ◽  
Dengwei Zhang ◽  
Xiaosen Jiang ◽  
Jie Li ◽  
...  
Keyword(s):  
Cerebral Cortex ◽  
Single Cell ◽  
Developmental Trajectories ◽  
Expression Patterns ◽  
Development Stage ◽  
Inhibitory Neurons ◽  
Projection Neurons ◽  
Cerebral Cortex Development ◽  
Excitatory Neurons ◽  
Human And Mouse

AbstractBackgroundThe specification and differentiation of neocortical projection neurons is a complex process under precise molecular regulation; however, little is known about the similarities and differences in cerebral cortex development between human and mouse at single-cell resolution.ResultsHere, using single-cell RNA-seq (scRNA-seq) data we explore the divergence and conservation of human and mouse cerebral cortex development using 18,446 and 7,610 neocortical cells. Systematic cross-species comparison reveals that the overall transcriptome profile in human cerebral cortex is similar to that in mouse such as cell types and their markers genes. By single-cell trajectories analysis we find human and mouse excitatory neurons have different developmental trajectories of neocortical projection neurons, ligand-receptor interactions and gene expression patterns. Further analysis reveals a refinement of neuron differentiation that occurred in human but not in mouse, suggesting that excitatory neurons in human undergo refined transcriptional states in later development stage. By contrast, for glial cells and inhibitory neurons we detected conserved developmental trajectories in human and mouse.ConclusionsTaken together, our study integrates scRNA-seq data of cerebral cortex development in human and mouse, and uncovers distinct developing models in neocortical projection neurons. The earlier activation of cognition -related genes in human may explain the differences in behavior, learning or memory abilities between the two species.

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