Heterogeneity of layer 4 in visual areas of rhesus macaque cortex.

Recently, single-cell RNA-sequencing (scRNA-seq) has enabled unprecedented insights to the cellular landscape of the brains of many different species, among them the rhesus macaque as a key animal model. Building on previous, broader surveys of the macaque brain, we closely examined five immediately neighboring areas within the visual cortex of the rhesus macaque: V1, V2, V4, MT and TEO. To facilitate this, we first devised a novel pipeline for brain spatial archive - the BrainSPACE - which enabled robust archiving and sampling from the whole unfixed brain. SnRNA-sequencing of ~100,000 nuclei from visual areas V1 and V4 revealed conservation within the GABAergic neuron subtypes, while seven and one distinct principle neuron subtypes were detected in V1 and V4, respectively, all most likely located in layer 4. Moreover, using small molecule fluorescence in situ hybridization, we identified cell type density gradients across V1, V2, V4, MT, and TEO appearing to reflect the visual hierarchy. These findings demonstrate an association between the clear areal specializations among neighboring areas with the hierarchical levels within the visual cortex of the rhesus macaque.

Top-down modulation of visual cortical stimulus encoding and gamma independent of firing rates.

Neurons in primary visual cortex integrate sensory input with signals reflecting the animal's internal state to support flexible behavior. Internal variables, such as expectation, attention, or current goals, are imposed in a top-down manner via extensive feedback projections from higher-order areas. We optogenetically activated a high-order visual area, area 21a, in the lightly anesthetized cat (OptoTD), while recording from neuronal populations in V1. OptoTD induced strong, up to several fold, changes in gamma-band synchronization together with much smaller changes in firing rate, and the two effects showed no correlation. OptoTD effects showed specificity for the features of the simultaneously presented visual stimuli. OptoTD-induced changes in gamma synchronization, but not firing rates, were predictive of simultaneous changes in the amount of encoded stimulus information. Our findings suggest that one important role of top-down signals is to modulate synchronization and the information encoded by populations of sensory neurons.

Cortical gamma-band resonance preferentially transmits coherent input.

Synchronization has been implicated in neuronal communication, but causal evidence remains indirect. We use optogenetics to generate depolarizing currents in pyramidal neurons of the cat visual cortex, emulating excitatory synaptic inputs under precise temporal control, while measuring spike output. The cortex transforms constant excitation into strong gamma-band synchronization, revealing the well-known cortical resonance. Increasing excitation with ramps increases the strength and frequency of synchronization. Slow, symmetric excitation profiles reveal hysteresis of power and frequency. White-noise input sequences enable causal analysis of network transmission, establishing that the cortical gamma-band resonance preferentially transmits coherent input components. Models composed of recurrently coupled excitatory and inhibitory units uncover a crucial role of feedback inhibition and suggest that hysteresis can arise through spike-frequency adaptation. The presented approach provides a powerful means to investigate the resonance properties of local circuits and probe how these properties transform input and shape transmission.

Callosal Influence on Visual Receptive Fields Has an Ocular, an Orientation-and Direction Bias.

One leading hypothesis on the nature of visual callosal connections (CC) is that they replicate features of intrahemispheric lateral connections. However, CC act also in the central part of the binocular visual field. In agreement, early experiments in cats indicated that they provide the ipsilateral eye part of binocular receptive fields (RFs) at the vertical midline (Berlucchi and Rizzolatti, 1968), and play a key role in stereoscopic function. But until today callosal inputs to receptive fields activated by one or both eyes were never compared simultaneously, because callosal function has been often studied by cutting or lesioning either corpus callosum or optic chiasm not allowing such a comparison. To investigate the functional contribution of CC in the intact cat visual system we recorded both monocular and binocular neuronal spiking responses and receptive fields in the 17/18 transition zone during reversible deactivation of the contralateral hemisphere. Unexpectedly from many of the previous reports, we observe no change in ocular dominance during CC deactivation. Throughout the transition zone, a majority of RFs shrink, but several also increase in size. RFs are significantly more affected for ipsi- as opposed to contralateral stimulation, but changes are also observed with binocular stimulation. Noteworthy, RF shrinkages are tiny and not correlated to the profound decreases of monocular and binocular firing rates. They depend more on orientation and direction preference than on eccentricity or ocular dominance of the receiving neuron's RF. Our findings confirm that in binocularly viewing mammals, binocular RFs near the midline are constructed via the direct geniculo-cortical pathway. They also support the idea that input from the two eyes complement each other through CC: Rather than linking parts of RFs separated by the vertical meridian, CC convey a modulatory influence, reflecting the feature selectivity of lateral circuits, with a strong cardinal bias.

Motion contrast in primary visual cortex: a direct comparison of single neuron and population encoding.

Features from outside the classical receptive field (CRF) can modulate the stimulus-driven activity of single cells in the primary visual cortex. This modulation, mediated by horizontal and feedback networks, has been extensively described as a variation of firing rate and is considered the basis of processing features as, for example, motion contrast. However, surround influences have also been identified in pairwise spiking or local field coherence. Yet, evidence about co-existence and integration of different neural signatures remains elusive. To compare multiple signatures, we recorded spiking and LFP activity evoked by stimuli exhibiting a motion contrast in the CRFs surround in anesthetized cat primary visual cortex. We chose natural-like scenes over gratings to avoid predominance of simple visual features, which could be easily represented by a rate code. We analyzed firing rates and phase-locking to low-gamma frequency in single cells and neuronal assemblies. Motion contrast was reflected in all measures but in semi-independent populations. Whereas activation of assemblies accompanied single neuron rates, their phase relations were modulated differently. Interestingly, only assembly phase relations mirrored the direction of movement of the surround and were selectively affected by thermal deactivation of visual interhemispheric connections. We argue that motion contrast can be reflected in complementary and superimposed neuronal signatures that can represent different surround features in independent neuronal populations.

In Vivo Magnetic Recording of Neuronal Activity.

Neuronal activity generates ionic flows and thereby both magnetic fields and electric potential differences, i.e., voltages. Voltage measurements are widely used but suffer from isolating and smearing properties of tissue between source and sensor, are blind to ionic flow direction, and reflect the difference between two electrodes, complicating interpretation. Magnetic field measurements could overcome these limitations but have been essentially limited to magnetoencephalography (MEG), using centimeter-sized, helium-cooled extracranial sensors. Here, we report on in vivo magnetic recordings of neuronal activity from visual cortex of cats with magnetrodes, specially developed needle-shaped probes carrying micron-sized, non-cooled magnetic sensors based on spin electronics. Event-related magnetic fields inside the neuropil were on the order of several nanoteslas, informing MEG source models and efforts for magnetic field measurements through MRI. Though the signal-to-noise ratio is still inferior to electrophysiology, this proof of concept demonstrates the potential to exploit the fundamental advantages of magnetophysiology.

Selective interhemispheric circuits account for a cardinal bias in spontaneous activity within early visual areas.

Ongoing brain activity exhibits patterns resembling neural ensembles co-activated by stimulation or task performance. Such patterns have been attributed to the brain's functional architecture, e.g. selective long-range connections. Here, we directly investigate the contribution of selective connections between hemispheres to spontaneous and evoked maps in cat area 18 close to the 17/18 border. We recorded voltage-sensitive dye imaging maps and spiking activity while manipulating interhemispheric input by reversibly deactivating corresponding contralateral areas. During deactivation, spontaneous maps continued to be generated with similar frequency and quality as in the intact network but a baseline cardinal bias disappeared. Consistently, neurons preferring either horizontal (HN) or vertical (VN), as opposed to oblique contours, decreased their resting state activity. HN decreased their rates also when stimulated visually. We conclude that structured spontaneous maps are primarily generated by thalamo- and/or intracortical connectivity. However, selective long-range connections through the corpus callosum - in perpetuation of the long-range intracortical network - contribute to a cardinal bias, possibly, because they are stronger or more frequent between neurons preferring horizontal and/or cardinal contours. As those contours are easier perceived and appear more frequently in natural environment, long-range connections might provide visual cortex with a grid for probabilistic grouping operations in a larger visual scene.

Gamma-Rhythmic Gain Modulation.

Cognition requires the dynamic modulation of effective connectivity, i.e., the modulation of the postsynaptic neuronal response to a given input. If postsynaptic neurons are rhythmically active, this might entail rhythmic gain modulation, such that inputs synchronized to phases of high gain benefit from enhanced effective connectivity. We show that visually induced gamma-band activity in awake macaque area V4 rhythmically modulates responses to unpredictable stimulus events. This modulation exceeded a simple additive superposition of a constant response onto ongoing gamma-rhythmic firing, demonstrating the modulation of multiplicative gain. Gamma phases leading to strongest neuronal responses also led to shortest behavioral reaction times, suggesting functional relevance of the effect. Furthermore, we find that constant optogenetic stimulation of anesthetized cat area 21a produces gamma-band activity entailing a similar gain modulation. As the gamma rhythm in area 21a did not spread backward to area 17, this suggests that postsynaptic gamma is sufficient for gain modulation.

A Statistical Framework to Infer Delay and Direction of Information Flow from Measurements of Complex Systems.

In neuroscience, data are typically generated from neural network activity. The resulting time series represent measurements from spatially distributed subsystems with complex interactions, weakly coupled to a high-dimensional global system. We present a statistical framework to estimate the direction of information flow and its delay in measurements from systems of this type. Informed by differential topology, gaussian process regression is employed to reconstruct measurements of putative driving systems from measurements of the driven systems. These reconstructions serve to estimate the delay of the interaction by means of an analytical criterion developed for this purpose. The model accounts for a range of possible sources of uncertainty, including temporally evolving intrinsic noise, while assuming complex nonlinear dependencies. Furthermore, we show that if information flow is delayed, this approach also allows for inference in strong coupling scenarios of systems exhibiting synchronization phenomena. The validity of the method is demonstrated with a variety of delay-coupled chaotic oscillators. In addition, we show that these results seamlessly transfer to local field potentials in cat visual cortex.

Input and output gain modulation by the lateral interhemispheric network in early visual cortex.

Neurons in the cerebral cortex are constantly integrating different types of inputs. Dependent on their origin, these inputs can be modulatory in many ways and, for example, change the neuron's responsiveness, sensitivity, or selectivity. To investigate the modulatory role of lateral input from the same level of cortical hierarchy, we recorded in the primary visual cortex of cats while controlling synaptic input from the corresponding contralateral hemisphere by reversible deactivation. Most neurons showed a pronounced decrease in their response to a visual stimulus of different contrasts and orientations. This indicates that the lateral network acts via an unspecific gain-setting mechanism, scaling the output of a neuron. However, the interhemispheric input also changed the contrast sensitivity of many neurons, thereby acting on the input. Such a contrast gain mechanism has important implications because it extends the role of the lateral network from pure response amplification to the modulation of a specific feature. Interestingly, for many neurons, we found a mixture of input and output gain modulation. Based on these findings and the known physiology of callosal connections in the visual system, we developed a simple model of lateral interhemispheric interactions. We conclude that the lateral network can act directly on its target, leading to a sensitivity change of a specific feature, while at the same time it also can act indirectly, leading to an unspecific gain setting. The relative contribution of these direct and indirect network effects determines the outcome for a particular neuron.

An updated midline rule: visual callosal connections anticipate shape and motion in ongoing activity across the hemispheres.

It is generally thought that callosal connections (CCs) in primary visual cortices serve to unify the visual scenery parted in two at the vertical midline (VM). Here, we present evidence that this applies also to visual features that do not cross yet but might cross the VM in the future. During reversible deactivation of the contralateral visual cortex in cats, we observed that ipsilaterally recorded neurons close to the border between areas 17 and 18 receive selective excitatory callosal input on both ongoing and evoked activity. In detail, neurons responding well to a vertical Gabor patch moving away from the deactivated hemifield decreased prestimulus and stimulus-driven activity much more than those preferring motion toward the cooled hemifield. Further, activity of neurons responding to horizontal lines decreased more than the response to vertical lines. Embedding a single Gabor into a collinear line context selectively stabilized responses, especially when the context was limited to the intact hemifield. These findings indicate that CCs interconnect not only neurons coding for similar orientations but also for similar directions of motion. We conclude that CCs anticipate stimulus features that are potentially relevant for both hemifields (i.e., coherent motion but also collinear shape) because already prestimulus activity and activity to stimuli not crossing the VM revealed feature specificity. Finally, we hypothesize that intrinsic and callosal networks processing different orientations and directions are anisotropic close to the VM facilitating perceptual grouping along likely future motion or (shape) trajectories before the visual stimulus arrives.

Multiplicative mechanism of lateral interactions revealed by controlling interhemispheric input.

Long-range horizontal connections are thought to modulate the responsiveness of neurons by supplying contextual information. A special type of long-range connections are interhemispheric projections, linking the 2 cerebral hemispheres. To investigate the action of those projections in a causal approach, we recorded in cat primary visual cortex while deactivating corresponding regions on the contralateral hemisphere. Interestingly, the action of callosal projections turned out to depend on the local and global composition of the stimulus: Full-field stimulation with gratings revealed moderate rate decreases (modulation index -0.24) and some significant increases (+0.21), whereas with lesser salient random dot textures, much more neurons were affected and reacted with pronounced rate decreases (-0.4). However, orientation and direction selectivity of those neurons were only slightly influenced by callosal input. This invariance could be achieved by scaling responses multiplicatively. Indeed, we could quantify the action of callosal input as a multiplicative scaling of responses, but additive scaling also occurred, especially for grating stimulation. We conclude that the quantitative action of long-range horizontal connections is by no means fixed but depends on how the network is driven by an external stimulus. Qualitatively, those connections seem to adjust the response gain of neurons, thereby preserving their selectivity.

Visual cortex combines a stimulus and an error-like signal with a proportion that is dependent on time, space, and stimulus contrast.

Even though the visual cortex is one of the most studied brain areas, the neuronal code in this area is still not fully understood. In the literature, two codes are commonly hypothesized, namely stimulus and predictive (error) codes. Here, we examined whether and how these two codes can coexist in a neuron. To this end, we assumed that neurons could predict a constant stimulus across time or space, since this is the most fundamental type of prediction. Prediction was examined in time using electrophysiology and voltage-sensitive dye imaging in the supragranular layers in area 18 of the anesthetized cat, and in space using a computer model. The distinction into stimulus and error code was made by means of the orientation tuning of the recorded unit. The stimulus was constructed as such that a maximum response to the non-preferred orientation indicated an error signal, and the maximum response to the preferred orientation indicated a stimulus signal. We demonstrate that a single neuron combines stimulus and error-like coding. In addition, we observed that the duration of the error coding varies as a function of stimulus contrast. For low contrast the error-like coding was prolonged by around 60-100%. Finally, the combination of stimulus and error leads to a suboptimal free energy in a recent predictive coding model. We therefore suggest a straightforward modification that can be applied to the free energy model and other predictive coding models. Combining stimulus and error might be advantageous because the stimulus code enables a direct stimulus recognition that is free of assumptions whereas the error code enables an experience dependent inference of ambiguous and non-salient stimuli.