Non-linear population firing rates and voltage sensitive dye signals in visual areas 17 and 18 to short duration stimuli

In silico voltage-sensitive dye imaging reveals the emergent dynamics of cortical populations

Voltage-sensitive dye imaging (VSDI) is a powerful technique for interrogating membrane potential dynamics in assemblies of cortical neurons, but with effective resolution limits that confound interpretation. To address this limitation, we developed an in silico model of VSDI in a biologically faithful digital reconstruction of rodent neocortical microcircuitry. Using this model, we extend previous experimental observations regarding the cellular origins of VSDI, finding that the signal is driven primarily by neurons in layers 2/3 and 5, and that VSDI measurements do not capture individual spikes. Furthermore, we test the capacity of VSD image sequences to discriminate between afferent thalamic inputs at various spatial locations to estimate a lower bound on the functional resolution of VSDI. Our approach underscores the power of a bottom-up computational approach for relating scales of cortical processing.

Saccade-based termination responses in macaque V1 and visual perception

Neurons in visual areas of the brain are generally characterized by the increase in firing rate that occurs when a stimulus is flashed on in the receptive field (RF). However, neurons also increase their firing rate when a stimulus is turned off. These "termination responses" or "after-discharges" that occur with flashed stimuli have been observed in area V1 and they may be important for vision as stimulus terminations have been shown to influence visual perception. The goal of the present study was to determine the strength of termination responses in the more natural situation in which eye movements move a stimulus out of an RF. We find that termination responses do occur in macaque V1 when termination results from a saccadic eye movement, but they are smaller in amplitude compared to flashed-off stimuli. Furthermore, there are termination responses even in the absence of visual stimulation. These findings demonstrate that termination responses are a component of naturalistic vision. They appear to be based on both visual and nonvisual signals in visual cortex. We speculate that the weakening of termination responses might be a neural correlate of saccadic suppression, the loss of perceptual sensitivity around the time of saccades.

Space-Time Dynamics of Membrane Currents Evolve to Shape Excitation, Spiking, and Inhibition in the Cortex at Small and Large Scales

In the cerebral cortex, membrane currents, i.e., action potentials and other membrane currents, express many forms of space-time dynamics. In the spontaneous asynchronous irregular state, their space-time dynamics are local non-propagating fluctuations and sparse spiking appearing at unpredictable positions. After transition to active spiking states, larger structured zones with active spiking neurons appear, propagating through the cortical network, driving it into various forms of widespread excitation, and engaging the network from microscopic scales to whole cortical areas. At each engaged cortical site, the amount of excitation in the network, after a delay, becomes matched by an equal amount of space-time fine-tuned inhibition that might be instrumental in driving the dynamics toward perception and action.

Breaking the Excitation-Inhibition Balance Makes the Cortical Network's Space-Time Dynamics Distinguish Simple Visual Scenes

Brain dynamics are often taken to be temporal dynamics of spiking and membrane potentials in a balanced network. Almost all evidence for a balanced network comes from recordings of cell bodies of few single neurons, neglecting more than 99% of the cortical network. We examined the space-time dynamics of excitation and inhibition simultaneously in dendrites and axons over four visual areas of ferrets exposed to visual scenes with stationary and moving objects. The visual stimuli broke the tight balance between excitation and inhibition such that the network exhibited longer episodes of net excitation subsequently balanced by net inhibition, in contrast to a balanced network. Locally in all four areas the amount of net inhibition matched the amount of net excitation with a delay of 125 ms. The space-time dynamics of excitation-inhibition evolved to reduce the complexity of neuron interactions over the whole network to a flow on a low-(3)-dimensional manifold within 80 ms. In contrast to the pure temporal dynamics, the low dimensional flow evolved to distinguish the simple visual scenes.

An investigation of the spatial selectivity of the duration after-effect

Adaptation to the duration of a visual stimulus causes the perceived duration of a subsequently presented stimulus with a slightly different duration to be skewed away from the adapted duration. This pattern of repulsion following adaptation is similar to that observed for other visual properties, such as orientation, and is considered evidence for the involvement of duration-selective mechanisms in duration encoding. Here, we investigated whether the encoding of duration - by duration-selective mechanisms - occurs early on in the visual processing hierarchy. To this end, we investigated the spatial specificity of the duration after-effect in two experiments. We measured the duration after-effect at adapter-test distances ranging between 0 and 15° of visual angle and for within- and between-hemifield presentations. We replicated the duration after-effect: the test stimulus was perceived to have a longer duration following adaptation to a shorter duration, and a shorter duration following adaptation to a longer duration. Importantly, this duration after-effect occurred at all measured distances, with no evidence for a decrease in the magnitude of the after-effect at larger distances or across hemifields. This shows that adaptation to duration does not result from adaptation occurring early on in the visual processing hierarchy. Instead, it seems likely that duration information is a high-level stimulus property that is encoded later on in the visual processing hierarchy.

Appearance of fast astrocytic component in voltage-sensitive dye imaging of neural activity

Background

Voltage-sensitive dye (VSD) imaging and intrinsic optical signals (IOS) are widely used methods for monitoring spatiotemporal neural activity in extensive networks. In spite of that, identification of their major cellular and molecular components has not been concluded so far.

Results

We addressed these issues by imaging spatiotemporal spreading of IOS and VSD transients initiated by Schaffer collateral stimulation in rat hippocampal slices with temporal resolution comparable to standard field potential recordings using a 464-element photodiode array. By exploring the potential neuronal and astroglial molecular players in VSD and IOS generation, we identified multiple astrocytic mechanisms that significantly contribute to the VSD signal, in addition to the expected neuronal targets. Glutamate clearance through the astroglial glutamate transporter EAAT2 has been shown to be a significant player in VSD generation within a very short (<5 ms) time-scale, indicating that astrocytes do contribute to the development of spatiotemporal VSD transients previously thought to be essentially neuronal. In addition, non-specific anion channels, astroglial K⁺ clearance through K_ir4.1 channel and astroglial Na⁺/K⁺ ATPase also contribute to IOS and VSD transients.

Conclusion

VSD imaging cannot be considered as a spatially extended field potential measurement with predominantly neuronal origin, instead it also reflects a fast communication between neurons and astrocytes.

Primary visual cortex represents the difference between past and present

The visual system is confronted with rapidly changing stimuli in everyday life. It is not well understood how information in such a stream of input is updated within the brain. We performed voltage-sensitive dye imaging across the primary visual cortex (V1) to capture responses to sequences of natural scene contours. We presented vertically and horizontally filtered natural images, and their superpositions, at 10 or 33 Hz. At low frequency, the encoding was found to represent not the currently presented images, but differences in orientation between consecutive images. This was in sharp contrast to more rapid sequences for which we found an ongoing representation of current input, consistent with earlier studies. Our finding that for slower image sequences, V1 does no longer report actual features but represents their relative difference in time counteracts the view that the first cortical processing stage must always transfer complete information. Instead, we show its capacities for change detection with a new emphasis on the role of automatic computation evolving in the 100-ms range, inevitably affecting information transmission further downstream.

Voltage-sensitive dye imaging of primary motor cortex activity produced by ventral tegmental area stimulation

The primary motor cortex (M1) receives dopaminergic projections from the ventral tegmental area (VTA) through the mesocortical dopamine pathway. However, few studies have focused on changes in M1 neuronal activity caused by VTA activation. To address this issue, we used voltage-sensitive dye imaging (VSD) to reveal the spatiotemporal dynamics of M1 activity induced by single-pulse stimulation of VTA in anesthetized rats. VSD imaging showed that brief electrical stimulation of unilateral VTA elicited a short-latency excitatory-inhibitory sequence of neuronal activity not only in the ipsilateral but also in the contralateral M1. The contralateral M1 response was not affected by pharmacological blockade of ipsilateral M1 activity, but it was completely abolished by corpus callosum transection. Although the VTA-evoked neuronal activity extended throughout the entire M1, we found the most prominent activity in the forelimb area of M1. The 6-OHDA-lesioned VTA failed to evoke M1 activity. Furthermore, both excitatory and inhibitory intact VTA-induced activity was entirely extinguished by blocking glutamate receptors in the target M1. When intracortical microstimulation of M1 was paired with VTA stimulation, the evoked forelimb muscle activity was facilitated or inhibited, depending on the interval between the two stimuli. These findings suggest that VTA neurons directly modulate the excitability of M1 neurons via fast glutamate signaling and, consequently, may control the last cortical stage of motor command processing.

Cortico-cortical communication dynamics

In principle, cortico-cortical communication dynamics is simple: neurons in one cortical area communicate by sending action potentials that release glutamate and excite their target neurons in other cortical areas. In practice, knowledge about cortico-cortical communication dynamics is minute. One reason is that no current technique can capture the fast spatio-temporal cortico-cortical evolution of action potential transmission and membrane conductances with sufficient spatial resolution. A combination of optogenetics and monosynaptic tracing with virus can reveal the spatio-temporal cortico-cortical dynamics of specific neurons and their targets, but does not reveal how the dynamics evolves under natural conditions. Spontaneous ongoing action potentials also spread across cortical areas and are difficult to separate from structured evoked and intrinsic brain activity such as thinking. At a certain state of evolution, the dynamics may engage larger populations of neurons to drive the brain to decisions, percepts and behaviors. For example, successfully evolving dynamics to sensory transients can appear at the mesoscopic scale revealing how the transient is perceived. As a consequence of these methodological and conceptual difficulties, studies in this field comprise a wide range of computational models, large-scale measurements (e.g., by MEG, EEG), and a combination of invasive measurements in animal experiments. Further obstacles and challenges of studying cortico-cortical communication dynamics are outlined in this critical review.

Laminar firing and membrane dynamics in four visual areas exposed to two objects moving to occlusion

It is not known how visual cortical neurons react to several moving objects and how their firing to the motion of one object is affected by neurons firing to another moving object. Here we combine imaging of voltage sensitive dye (VSD) signals, reflecting the population membrane potential from ferret visual areas 17, 18, 19, and 21, with laminar recordings of multiunit activity, (MUA), when two bars moved toward each other in the visual field, occluded one another, and continued on in opposite directions. Two zones of peak MUA, mapping the bars' motion, moved toward each other along the area 17/18 border, which in the ferret maps the vertical meridian of the field of view. This was reflected also in the VSD signal, at both the 17/18 border as well as at the 19/21 border with a short delay. After some 125 ms at the area 19/21 border, the VSD signal increased and became elongated in the direction of motion in front of both of the moving representations. This was directly followed by the phase of the signal reversing and travelling back from the 19/21 border toward the 17/18 border, seemingly without respect for retinotopic boundaries, where it arrived at 150 ms after stimulus onset. At this point the VSD signal in front of the moving bar representations along the 17/18 border also increased and became elongated in the direction of object motion; the signal now being the linear sum of what has been observed in response to single moving bars. When the neuronal populations representing the bars were some 600 μm apart on the cortex, the dye signal and laminar MUA decreased strongly, with the MUA scaling to that of a single bar during occlusion. Despite a short rebound of the dye signal and MUA, the MUA after the occlusion was significantly depressed. The interactions between the neuronal populations mapping the bars' position, and the neurons in between these populations were, apart from 19/21 to 17/18 interaction, mainly lateral-horizontal; first excitatory and inducing firing at the site of future occlusion, then inhibitory just prior to occlusion. After occlusion the neurons that had fired already to the first bar showed delayed and prolonged inhibition in response to the second bar. Thus, the interactions that were particular to the occlusion condition in these experiments were local and inhibitory at short cortical range, and delayed and inhibitory after the occlusion when the bars moved further apart.

Cortical long-range interactions embed statistical knowledge of natural sensory input: a voltage-sensitive dye imaging study

How is contextual processing as demonstrated with simplified stimuli, cortically enacted in response to ecologically relevant complex and dynamic stimuli? Using voltage-sensitive dye imaging, we captured mesoscopic population dynamics across several square millimeters of cat primary visual cortex. By presenting natural movies locally through either one or two adjacent apertures, we show that simultaneous presentation leads to mutual facilitation of activity. These synergistic effects were most effective when both movie patches originated from the same natural movie, thus forming a coherent stimulus in which the inherent spatio-temporal structure of natural movies were preserved in accord with Gestalt principles of perceptual organization. These results suggest that natural sensory input triggers cooperative mechanisms that are imprinted into the cortical functional architecture as early as in primary visual cortex.

Six principles of visual cortical dynamics

A fundamental goal in vision science is to determine how many neurons in how many areas are required to compute a coherent interpretation of the visual scene. Here I propose six principles of cortical dynamics of visual processing in the first 150 ms following the appearance of a visual stimulus. Fast synaptic communication between neurons depends on the driving neurons and the biophysical history and driving forces of the target neurons. Under these constraints, the retina communicates changes in the field of view driving large populations of neurons in visual areas into a dynamic sequence of feed-forward communication and integration of the inward current of the change signal into the dendrites of higher order area neurons (30-70 ms). Simultaneously an even larger number of neurons within each area receiving feed-forward input are pre-excited to sub-threshold levels. The higher order area neurons communicate the results of their computations as feedback adding inward current to the excited and pre-excited neurons in lower areas. This feedback reconciles computational differences between higher and lower areas (75-120 ms). This brings the lower area neurons into a new dynamic regime characterized by reduced driving forces and sparse firing reflecting the visual areas interpretation of the current scene (140 ms). The population membrane potentials and net-inward/outward currents and firing are well behaved at the mesoscopic scale, such that the decoding in retinotopic cortical space shows the visual areas' interpretation of the current scene. These dynamics have plausible biophysical explanations. The principles are theoretical, predictive, supported by recent experiments and easily lend themselves to experimental tests or computational modeling.

Relating information, encoding and adaptation: decoding the population firing rate in visual areas 17/18 in response to a stimulus transition

Neurons in the primary visual cortex typically reach their highest firing rate after an abrupt image transition. Since the mutual information between the firing rate and the currently presented image is largest during this early firing period it is tempting to conclude this early firing encodes the current image. This view is, however, made more complicated by the fact that the response to the current image is dependent on the preceding image. Therefore we hypothesize that neurons encode a combination of current and previous images, and that the strength of the current image relative to the previous image changes over time. The temporal encoding is interesting, first, because neurons are, at different time points, sensitive to different features such as luminance, edges and textures; second, because the temporal evolution provides temporal constraints for deciphering the instantaneous population activity. To study the temporal evolution of the encoding we presented a sequence of 250 ms stimulus patterns during multiunit recordings in areas 17 and 18 of the anaesthetized ferret. Using a novel method we decoded the pattern given the instantaneous population-firing rate. Following a stimulus transition from stimulus A to B the decoded stimulus during the first 90ms was more correlated with the difference between A and B (B-A) than with B alone. After 90ms the decoded stimulus was more correlated with stimulus B than with B-A. Finally we related our results to information measures of previous (B) and current stimulus (A). Despite that the initial transient conveys the majority of the stimulus-related information; we show that it actually encodes a difference image which can be independent of the stimulus. Only later on, spikes gradually encode the stimulus more exclusively.

The role of multi-area interactions for the computation of apparent motion

Apparent motion (AM) is a robust visual illusion, in which fast displays of static objects in successively different positions elicit the perception of object motion. Neurons in higher order areas 21 and 19 compute object motion under such conditions and send feedback to early visual areas 18 and 17, which is instrumental in eliciting computation of motion in those very areas. To explore the computational dynamics of AM, we made a neural field model consisting of two one-dimensional rings of simple neurons expressing firing rates, one for areas 17/18 and one for areas 19/21. The model neurons, without any orientation or direction selectivity, computed apparent motion for the range of space-timings of stimuli associated with short- and long-range AM in humans. The computation of long-range AM in 17/18 required two model areas and the presence of feedback and conduction/computation delays between those areas. As in the in vivo experiments of long-range AM, the stationary stimuli were initially mapped as stationary in model area 17/18, but after the feedback also these lower areas computed AM. The dynamics of the two-area network produces short-range and long-range apparent motion for a large range of feedback strengths and a small range of lateral excitation near the bifurcation to an amplitude instability. The computation of AM in higher order areas was due to the neurons in these areas having large receptive fields as a consequence of divergent feed-forward connectivity. This implies that these areas compute long-range AM when early areas 17 and 18 do not, and therefore higher order areas must enslave lower order areas to compute the same, if the whole network is to arrive at a coherent perceptual solution.