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Seidemann, E.

Publications and source records attributed to Seidemann, E..

8 recordsLinked to original sources

Wide dynamic range of contrast-encoding in neural responses in macaque V1

The dynamic range of contrast-encoding in the early visual system has been investigated at both single-neuron and population levels in animals using oriented stimuli such as gratings and Gabor patches. However, contrast-encoding of unoriented stimuli such as Gaussians has been less explored, even though such stimuli can evoke a large population response. In studies that employ Gaussians, contrast response functions (CRFs) of neurons and neural populations in primary visual cortex are typically characterized across a limited range of Weber contrasts up to 100%, which may not adequately reflect the statistics of contrast in natural scenes. Indeed, our analysis shows that locations with contrasts far exceeding 100% Weber contrast are ubiquitous in natural scenes. Thus, our current understanding of contrast encoding remains incomplete in the context of natural environments. Here, we measured spiking activities of individual neurons using electrophysiology and population responses using calcium imaging in V1 of fixating macaques while Gaussian stimuli were presented over a wide range of Weber contrasts, up to 900%. Both the average spiking response and the average population response continued to increase robustly above 100% Weber contrast. Only a small minority of neurons saturate below 100% Weber contrast. These results demonstrate that the dynamic range of contrast-encoding in V1 is broader than previously assumed and aligns more closely with the statistics of contrast in natural scenes. Significance StatementThe dynamic range of contrast-encoding in V1 has typically been characterized using only a limited range of contrasts, often excluding the high contrasts commonly found in natural scenes. We measured contrast response functions of individual neurons and neural populations in V1 across a much wider range of contrasts. We found that the responses of the majority of neurons, as well as the overall population, increased robustly up to extremely high contrasts. These findings suggest that the dynamic range of contrast encoding in V1 extends well beyond the commonly tested range.

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Neural Correlates of Perceptual Similarity Masking in Primate V1

Visual detection is a fundamental natural task. Detection becomes more challenging as the similarity between the target and the background in which it is embedded increases, a phenomenon termed "similarity masking". To test the hypothesis that V1 contributes to similarity masking, we used voltage sensitive dye imaging (VSDI) to measure V1 population responses while macaque monkeys performed a detection task under varying levels of target-background similarity. Paradoxically, we find that during an initial transient phase, V1 responses to the target are enhanced, rather than suppressed, by target-background similarity. This effect reverses in the second phase of the response, so that in this phase V1 signals are positively correlated with the behavioral effect of similarity. Finally, we show that a simple model with delayed divisive normalization can qualitatively account for our findings. Overall, our results support the hypothesis that a nonlinear gain control mechanism in V1 contributes to perceptual similarity masking.

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Exact analysis of the subthreshold variability for conductance-based neuronal models with synchronous synaptic inputs

The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks operate in the asynchronous state. In the asynchronous state neurons fire independently from one another, so that the probability that a neuron experience synchronous synaptic inputs is exceedingly low. While the models of asynchronous neurons lead to observed spiking variability, it is not clear whether the asynchronous state can also account for the level of subthreshold membrane potential variability. We propose a new analytical framework to rigorously quantify the subthreshold variability of a single conductance-based neuron in response to synaptic inputs with prescribed degrees of synchrony. Technically we leverage the theory of exchangeability to model input synchrony via jump-process-based synaptic drives; we then perform a moment analysis of the stationary response of a neuronal model with all-or-none conductances that neglects post-spiking reset. As a result, we produce exact, interpretable closed forms for the first two stationary moments of the membrane voltage, with explicit dependence on the input synaptic numbers, strengths, and synchrony. For biophysically relevant parameters, we find that the asynchronous regime only yields realistic subthreshold variability (voltage variance [~=]4-9mV2) when driven by a restricted number of large synapses, compatible with strong thalamic drive. By contrast, we find that achieving realistic subthreshold variability with dense cortico-cortical inputs requires including weak but nonzero input synchrony, consistent with measured pairwise spiking correlations. We also show that without synchrony, the neural variability averages out to zero for all scaling limits with vanishing synaptic weights, independent of any balanced state hypothesis. This result challenges the theoretical basis for mean-field theories of the asynchronous state.

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Delayed normalization model captures disparate nonlinear neural dynamics measured with different techniques in macaque and human V1

Neuronal representations throughout the primate visual system display a wide range of nonlinear dynamics in response to static visual stimuli. To understand the neural basis of visual perception, it is important to quantify these nonlinearities and to develop general models that allow one to predict response dynamics to visual stimuli with arbitrary temporal waveform. Voltage-sensitive dye imaging (VSDI) is a powerful method for measuring neural population responses from the cortex of awake, behaving, subjects. Here we used VSDI to measure the dynamics of neural population responses in macaque V1 to visual stimuli with a wide range of time courses. We found that beyond clear nonlinearities for briefly presented visual stimuli, stimulus-evoked VSDI responses are surprisingly near additive in time. These results are qualitatively different from neural dynamics to similar stimuli previously measured in human visual cortex using fMRI and electrocorticography (ECoG), which show strong sub-additivity in time. To test whether this discrepancy is specific to VSDI, a signal dominated by subthreshold neural activity, we repeated our measurements using a genetically encoded calcium indicator (GCaMP), a signal dominated by spiking activity. We found that GCaMP signals in macaque V1 are also near-additive. Therefore, the discrepancies in the degree of additivity between these different measurements are not attributed to the difference between sub- and supra-threshold neural response. Finally, we show that a simple yet flexible delayed normalization model can capture the dynamics of all of these measurements, suggesting that dynamic gain-control is an important mechanism contributing to neural processing in the brain.

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Similar neural and perceptual masking effects of low-power optogenetic stimulation in primate V1

Can direct stimulation of primate V1 substitute for a visual stimulus and mimic its perceptual effect? To address this question, we developed an optical-genetic toolkit to "read" neural population responses using widefield calcium imaging, while simultaneously using optogenetics to "write" neural responses into V1 of behaving macaques. We focused on the phenomenon of visual masking, where detection of a dim target is significantly reduced by a co-localized medium-brightness pedestal. Using our toolkit, we tested whether V1 optogenetic stimulation can recapitulate the perceptual masking effect of a visual pedestal. We find that, similar to a visual pedestal, low-power optostimulation can significantly reduce visual detection sensitivity, that a sublinear interaction between visual and optogenetic evoked V1 responses could account for this perceptual effect, and that these neural and behavioral effects are spatially selective. Our toolkit and results open the door for further exploration of perceptual substitutions by direct stimulation of sensory cortex.

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Similar masking effects of natural backgrounds on detection performances in humans, macaques, and macaque-V1 population responses

Visual systems evolve to process the stimuli that arise in the organisms natural environment and hence to fully understand the neural computations in the visual system it is important to measure behavioral and neural responses to natural visual stimuli. Here we measured psychometric and neurometric functions and thresholds in the macaque monkey for detection of a windowed sine-wave target in uniform backgrounds and in natural backgrounds of various contrasts. The neurometric functions and neurometric thresholds were obtained by near-optimal decoding of voltage-sensitive-dye-imaging (VSDI) responses at the retinotopic scale in primary visual cortex (V1). The results were compared with previous human psychophysical measurements made under the same conditions. We found that human and macaque behavioral thresholds followed the generalized Webers law as function of contrast, and that both the slopes and the intercepts of the threshold functions match each other up to a single scale factor. We also found that the neurometric thresholds followed the generalized Webers law and that the neurometric slopes and intercepts matched the behavioral slopes and intercepts up to a single scale factor. We conclude that human and macaque ability to detect targets in natural backgrounds are affected in the same way by background contrast, that these effects are consistent with population decoding at the retinotopic scale by down-stream circuits, and that the macaque monkey is an appropriate animal model for gaining an understanding of the neural mechanisms in humans for detecting targets in natural backgrounds. Finally, we discuss limitations of the current study and potential next steps. New & NoteworthyWe measured macaque detection performance in natural images and compared their performance to the detection sensitivity of neurophysiological responses recorded in the primary visual cortex (V1), and to the performance of human subjects. We found that (i) human and macaque behavioral performances are in quantitative agreement, (ii) are consistent with near-optimal decoding of V1 population responses. SignificanceNatural selection guarantees that neural computations will be matched to the task-relevant natural stimuli in the organisms environment, and thus it is crucial to measure behavioral and neural responses to natural stimuli. We measured the ability of macaque monkeys to detect targets in natural images and compared their performance to neurophysiological responses recorded in the macaques primary visual cortex (V1), and to the performance of humans under the same conditions. We found that (i) human and macaque behavioral performance are in quantitative agreement, (ii) are consistent with near-optimal population decoding of V1 neural responses, and (iii) that the macaque monkey is an appropriate animal model for gaining understanding of the neural mechanisms in humans for detecting targets in natural backgrounds.

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Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface

Calcium imaging has rapidly developed into a powerful tool for recording from large populations of neurons in vivo. Imaging in rhesus macaque motor cortex can enable the discovery of new principles of motor cortical function and can inform the design of next generation brain-computer interfaces (BCIs). Surface two-photon (2P) imaging, however, cannot presently access somatic calcium signals of neurons from all layers of macaque motor cortex due to photon scattering. Here, we demonstrate an implant and imaging system capable of chronic, motion-stabilized two-photon (2P) imaging of calcium signals from in macaques engaged in a motor task. By imaging apical dendrites, some of which originated from deep layer 5 neurons, as as well as superficial cell bodies, we achieved optical access to large populations of deep and superficial cortical neurons across dorsal premotor (PMd) and gyral primary motor (M1) cortices. Dendritic signals from individual neurons displayed tuning for different directions of arm movement, which was stable across many weeks. Combining several technical advances, we developed an optical BCI (oBCI) driven by these dendritic signals and successfully decoded movement direction online. By fusing 2P functional imaging with CLARITY volumetric imaging, we verify that an imaged dendrite, which contributed to oBCI decoding, originated from a putative Betz cell in motor cortical layer 5. This approach establishes new opportunities for studying motor control and designing BCIs.

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Majority of choice-related variability in perceptual decisions is present in early sensory cortex

While performing challenging perceptual tasks such as detecting a barely visible target, our perceptual reports vary across presentations of identical stimuli. This perceptual variability is presumably caused by neural variability in our brains. How much of the neural variability that correlates with the perceptual variability is present in the primary visual cortex (V1), the first cortical processing stage of visual information? To address this question, we recorded neural population responses from V1 using voltage-sensitive dye imaging while monkeys performed a challenging reaction-time visual detection task. We found that V1 population responses in the period leading to the decision correspond more closely to the monkeys report than to the visual stimulus. These results, together with a simple computational model that allows one to quantify the captured choice-related variability, suggest that most of this variability is present in V1 as additive noise, and that areas downstream to V1 contain relatively little independent choice-related variability.

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