Adaptation-induced sharpening of orientation tuning curves in the mouse visual cortex.

OBJECTIVE: Orientation selectivity is an emergent property of visual neurons across species with columnar and noncolumnar organization of the visual cortex. The emergence of orientation selectivity is more established in columnar cortical areas than in noncolumnar ones. Thus, how does orientation selectivity emerge in noncolumnar cortical areas after an adaptation protocol? Adaptation refers to the constant presentation of a nonoptimal stimulus (adapter) to a neuron under observation for a specific time. Previously, it had been shown that adaptation has varying effects on the tuning properties of neurons, such as orientation, spatial frequency, motion and so on. BASIC METHODS: We recorded the mouse primary visual neurons (V1) at different orientations in the control (preadaptation) condition. This was followed by adapting neurons uninterruptedly for 12 min and then recording the same neurons postadaptation. An orientation selectivity index (OSI) for neurons was computed to compare them pre- and post-adaptation. MAIN RESULTS: We show that 12-min adaptation increases the OSI of visual neurons ( n  = 113), that is, sharpens their tuning. Moreover, the OSI postadaptation increases linearly as a function of the OSI preadaptation. CONCLUSION: The increased OSI postadaptation may result from a specific dendritic neural mechanism, potentially facilitating the rapid learning of novel features.

Integration of landmark and saccade target signals in macaque frontal cortex visual responses.

Visual landmarks influence spatial cognition and behavior, but their influence on visual codes for action is poorly understood. Here, we test landmark influence on the visual response to saccade targets recorded from 312 frontal and 256 supplementary eye field neurons in rhesus macaques. Visual response fields are characterized by recording neural responses to various target-landmark combinations, and then we test against several candidate spatial models. Overall, frontal/supplementary eye fields response fields preferentially code either saccade targets (40%/40%) or landmarks (30%/4.5%) in gaze fixation-centered coordinates, but most cells show multiplexed target-landmark coding within intermediate reference frames (between fixation-centered and landmark-centered). Further, these coding schemes interact: neurons with near-equal target and landmark coding show the biggest shift from fixation-centered toward landmark-centered target coding. These data show that landmark information is preserved and influences target coding in prefrontal visual responses, likely to stabilize movement goals in the presence of noisy egocentric signals.

Adaptation-induced plasticity in the sensory cortex.

For medical and fundamental reasons, we need to understand adult brain plasticity at several levels: structural, physiological, and behavioral. Historically, brain plasticity has been mostly investigated by weakening or removing sensory inputs. The visual system has been extensively used because diminishing visual inputs, i.e., visual deprivation-induced plasticity, permits more tractable findings. The present review is centered on the reverse strategy, by imposing a novel stimulus, i.e., adaptation-induced plasticity. Adaptation refers to the constant (milliseconds to hours) presentation of a nonoptimal stimulus (adapter) within the receptive field (RF, spatial area that modulates neuronal firing) of the neuron under observation. We specifically focus on how adaptation impacts the tuning of visual neurons with other associated properties. After adaptation, visual cortical neurons respond robustly to the adapter (before adaptation it typically evokes feeble responses) by developing alternate tuning curves that outlast the adaptation time. Here, with dendritic structure as foundation, we synthesize a push-pull mechanism of development and acquisition of novel tuning curves following adaptation. We then explain how these changes apply at the global level across different brain regions and species with a short description of underlying neurochemical changes. Finally, we discuss physiopathological consequences and conclude with some gaps and questions that need to be addressed to further comprehend such neuroplasticity.

Integration of allocentric and egocentric visual information in a convolutional/multilayer perceptron network model of goal-directed gaze shifts.

Allocentric (landmark-centered) and egocentric (eye-centered) visual codes are fundamental for spatial cognition, navigation, and goal-directed movement. Neuroimaging and neurophysiology suggest these codes are initially segregated, but then reintegrated in frontal cortex for movement control. We created and validated a theoretical framework for this process using physiologically constrained inputs and outputs. To implement a general framework, we integrated a convolutional neural network (CNN) of the visual system with a multilayer perceptron (MLP) model of the sensorimotor transformation. The network was trained on a task where a landmark shifted relative to the saccade target. These visual parameters were input to the CNN, the CNN output and initial gaze position to the MLP, and a decoder transformed MLP output into saccade vectors. Decoded saccade output replicated idealized training sets with various allocentric weightings and actual monkey data where the landmark shift had a partial influence (R 2 = 0.8). Furthermore, MLP output units accurately simulated prefrontal response field shifts recorded from monkeys during the same paradigm. In summary, our model replicated both the general properties of the visuomotor transformations for gaze and specific experimental results obtained during allocentric-egocentric integration, suggesting it can provide a general framework for understanding these and other complex visuomotor behaviors.

Spatiotemporal Coding in the Macaque Supplementary Eye Fields: Landmark Influence in the Target-to-Gaze Transformation.

Eye-centered (egocentric) and landmark-centered (allocentric) visual signals influence spatial cognition, navigation, and goal-directed action, but the neural mechanisms that integrate these signals for motor control are poorly understood. A likely candidate for egocentric/allocentric integration in the gaze control system is the supplementary eye fields (SEF), a mediofrontal structure with high-level "executive" functions, spatially tuned visual/motor response fields, and reciprocal projections with the frontal eye fields (FEF). To test this hypothesis, we trained two head-unrestrained monkeys (Macaca mulatta) to saccade toward a remembered visual target in the presence of a visual landmark that shifted during the delay, causing gaze end points to shift partially in the same direction. A total of 256 SEF neurons were recorded, including 68 with spatially tuned response fields. Model fits to the latter established that, like the FEF and superior colliculus (SC), spatially tuned SEF responses primarily showed an egocentric (eye-centered) target-to-gaze position transformation. However, the landmark shift influenced this default egocentric transformation: during the delay, motor neurons (with no visual response) showed a transient but unintegrated shift (i.e., not correlated with the target-to-gaze transformation), whereas during the saccade-related burst visuomotor (VM) neurons showed an integrated shift (i.e., correlated with the target-to-gaze transformation). This differed from our simultaneous FEF recordings (Bharmauria et al., 2020), which showed a transient shift in VM neurons, followed by an integrated response in all motor responses. Based on these findings and past literature, we propose that prefrontal cortex incorporates landmark-centered information into a distributed, eye-centered target-to-gaze transformation through a reciprocal prefrontal circuit.

Synchrony and Complexity in State-Related EEG Networks: An Application of Spectral Graph Theory.

The brain may be considered as a synchronized dynamic network with several coherent dynamical units. However, concerns remain whether synchronizability is a stable state in the brain networks. If so, which index can best reveal the synchronizability in brain networks? To answer these questions, we tested the application of the spectral graph theory and the Shannon entropy as alternative approaches in neuroimaging. We specifically tested the alpha rhythm in the resting-state eye closed (rsEC) and the resting-state eye open (rsEO) conditions, a well-studied classical example of synchrony in neuroimaging EEG. Since the synchronizability of alpha rhythm is more stable during the rsEC than the rsEO, we hypothesized that our suggested spectral graph theory indices (as reliable measures to interpret the synchronizability of brain signals) should exhibit higher values in the rsEC than the rsEO condition. We performed two separate analyses of two different datasets (as elementary and confirmatory studies). Based on the results of both studies and in agreement with our hypothesis, the spectral graph indices revealed higher stability of synchronizability in the rsEC condition. The k-mean analysis indicated that the spectral graph indices can distinguish the rsEC and rsEO conditions by considering the synchronizability of brain networks. We also computed correlations among the spectral indices, the Shannon entropy, and the topological indices of brain networks, as well as random networks. Correlation analysis indicated that although the spectral and the topological properties of random networks are completely independent, these features are significantly correlated with each other in brain networks. Furthermore, we found that complexity in the investigated brain networks is inversely related to the stability of synchronizability. In conclusion, we revealed that the spectral graph theory approach can be reliably applied to study the stability of synchronizability of state-related brain networks.

Integration of Eye-Centered and Landmark-Centered Codes in Frontal Eye Field Gaze Responses.

The visual system is thought to separate egocentric and allocentric representations, but behavioral experiments show that these codes are optimally integrated to influence goal-directed movements. To test if frontal cortex participates in this integration, we recorded primate frontal eye field activity during a cue-conflict memory delay saccade task. To dissociate egocentric and allocentric coordinates, we surreptitiously shifted a visual landmark during the delay period, causing saccades to deviate by 37% in the same direction. To assess the cellular mechanisms, we fit neural response fields against an egocentric (eye-centered target-to-gaze) continuum, and an allocentric shift (eye-to-landmark-centered) continuum. Initial visual responses best-fit target position. Motor responses (after the landmark shift) predicted future gaze position but embedded within the motor code was a 29% shift toward allocentric coordinates. This shift appeared transiently in memory-related visuomotor activity, and then reappeared in motor activity before saccades. Notably, fits along the egocentric and allocentric shift continua were initially independent, but became correlated across neurons just before the motor burst. Overall, these results implicate frontal cortex in the integration of egocentric and allocentric visual information for goal-directed action, and demonstrate the cell-specific, temporal progression of signal multiplexing for this process in the gaze system.

Eye-head-hand coordination during visually guided reaches in head-unrestrained macaques.

Nonhuman primates have been used extensively to study eye-head coordination and eye-hand coordination, but the combination-eye-head-hand coordination-has not been studied. Our goal was to determine whether reaching influences eye-head coordination (and vice versa) in rhesus macaques. Eye, head, and hand motion were recorded in two animals with search coil and touch screen technology, respectively. Animals were seated in a customized "chair" that allowed unencumbered head motion and reaching in depth. In the reach condition, animals were trained to touch a central LED at waist level while maintaining central gaze and were then rewarded if they touched a target appearing at 1 of 15 locations in a 40° × 20° (visual angle) array. In other variants, initial hand or gaze position was varied in the horizontal plane. In similar control tasks, animals were rewarded for gaze accuracy in the absence of reach. In the Reach task, animals made eye-head gaze shifts toward the target followed by reaches that were accompanied by prolonged head motion toward the target. This resulted in significantly higher head velocities and amplitudes (and lower eye-in-head ranges) compared with the gaze control condition. Gaze shifts had shorter latencies and higher velocities and were more precise, despite the lack of gaze reward. Initial hand position did not influence gaze, but initial gaze position influenced reach latency. These results suggest that eye-head coordination is optimized for visually guided reach, first by quickly and accurately placing gaze at the target to guide reach transport and then by centering the eyes in the head, likely to improve depth vision as the hand approaches the target.NEW & NOTEWORTHY Eye-head and eye-hand coordination have been studied in nonhuman primates but not the combination of all three effectors. Here we examined the timing and kinematics of eye-head-hand coordination in rhesus macaques during a simple reach-to-touch task. Our most novel finding was that (compared with hand-restrained gaze shifts) reaching produced prolonged, increased head rotation toward the target, tending to center the binocular field of view on the target/hand.

The function of connectomes in encoding sensory stimuli.

The enormous number of neurons and the massive sum of connecting fibers linking them make the neural processes of encoding sensory signals extraordinarily complex, and this challenge is far from being elucidated. Simply stated, for the present paper, the question is - how does the brain encode complex images? Our proposal argues that modulation of strengths of functional relationships between firing neurons in relation to an input results in the formation of stimulus-salient functional connectomes. This type of connection/coupling strength is computed by performing cross correlograms (CCG) of spike trains between simultaneously firing cells. Significantly, the strength is dependent upon stimuli characteristics, inferring that cells may join or leave particular ensembles, thus creating signature emergent connectomes for different images, thereby, allowing their discrimination. We observed in an ensemble that functionally connected cells exhibited synergistic excitatory activity, increased coherence, and augmented gamma oscillations within a window-of-opportunity contrasting with unconnected neighboring neuronal companions. We suggest that investigating and revealing such stimulus-salient emergent connectomes is a realistic and promising pursuit toward answering how the brain processes complex images.

Sound Induces Change in Orientation Preference of V1 Neurons: Audio-Visual Cross-Influence.

In the cortex, demarcated unimodal sensory regions often respond to unforeseen sensory stimuli and exhibit plasticity. The goal of the current investigation was to test evoked responses of primary visual cortex (V1) neurons when an adapting auditory stimulus is applied in isolation. Using extracellular recordings in anesthetized cats, we demonstrate that, unlike the prevailing observation of only slight modulations in the firing rates of the neurons, sound imposition in isolation entirely shifted the peaks of orientation tuning curves of neurons in both supra- and infragranular layers of V1. Our results suggest that neurons specific to either layer dynamically integrate features of sound and modify the organization of the orientation map of V1. Intriguingly, these experiments present novel findings that the mere presentation of a prolonged auditory stimulus may drastically recalibrate the tuning properties of the visual neurons and highlight the phenomenal neuroplasticity of V1 neurons.

The dendritic tree: a mathematical integrator.

Neurons in the primary visual cortex (V1) are sensitive to simple features of the visual scene such as contrast, spatial frequency or orientations. In higher mammals, they are organized into columns of orientation-preference, whereas such organization is absent in rodents. However, in both types of organization, neurons can be highly selective or poorly selective for a particular stimulus. In mouse V1, it has been shown that all stimuli are represented on the dendritic tree of single neurons. To what extent this concept is applicable in higher mammals? In this review, we discuss possible models of integrating visual information from visual cortical neurons. In particular, how the modulation of the number of inputs and/or the frequency firing can explain the orientation selectivity in V1. Based on our findings and literature, we propose three different hypotheses namely the spatial summation, the temporal summation and the excitation-inhibition. In addition, we discuss the possible interactions between excitatory pyramidal neurons and inhibitory interneurons during stimulus processing.

Comparative effects of adaptation on layers II-III and V-VI neurons in cat V1.

V1 is fundamentally grouped into columns that descend from layers II-III to V-VI. Neurons inherent to visual cortex are capable of adapting to changes in the incoming stimuli that drive the cortical plasticity. A principle feature called orientation selectivity can be altered by the presentation of non-optimal stimulus called 'adapter'. When triggered, LGN cells impinge upon layer IV and further relay the information to deeper layers via layers II-III. Using different adaptation protocols, neuronal plasticity can be investigated. Superficial neurons in area V1 are well acknowledged to exhibit attraction and repulsion by shifting their tuning peaks when challenged by a non-optimal stimulus called 'adapter'. Layers V-VI neurons in spite of partnering layers II-III neurons in cortical computation have not been explored simultaneously toward adaptation. We believe that adaptation not only affects cells specific to a layer but modifies the entire column. In this study, through simultaneous multiunit recordings in anesthetized cats using a multichannel depth electrode, we show for the first time how layers V-VI neurons (1000-1200 µm) along with layers II-III neurons (300-500 µm) exhibit plasticity in response to adaptation. Our results demonstrate that superficial and deeper layer neurons react synonymously toward adapter by exhibiting similar behavioral properties. The neurons displayed similar amplitude of shift and maintained equivalent sharpness of Gaussian tuning peaks before and the following adaptation. It appears that a similar mechanism, belonging to all layers, is responsible for the analog outcome of the neurons' experience with adapter.

Functional synchrony and stimulus selectivity of visual cortical units: Comparison between cats and mice.

In spite of the fact that the functional organization of primary visual cortices (V1) differs across species, the dynamic of orientation selectivity is highly structured within neuronal populations. In fact, neurons functionally connect each other in an organized Hebbian process, wherein their wiring and firing are intimately related. Moreover, neuronal ensembles have been suggested to be strongly implicated in sensory processing. Within these ensembles, neurons may be sharply or broadly tuned in relation to the stimulus. Therefore, it is important to determine the relationship between the response selectivity of neurons and their functional connectivity pattern across species. In the present investigation, we sought to compare the stimulus-evoked functional connectivity between the broadly tuned and the sharply tuned neurons in two species exhibiting different cortical organization for orientation selectivity: cats (columnar-organized) and mice (salt-and-pepper organization). In addition, we examined the distribution of connectivity weights within cell-assemblies in the visual cortex during visual adaptation. First, we report that the sharply tuned neurons exhibited higher synchrony index than the broadly tuned cells in the cat visual cortex. On the contrary, in mice, the broadly tuned cells displayed higher connectivity index. Second, a significant correlation was found between the connectivity strength and the difference of preferred orientations of neurons for both species. Finally, we observed a systematic adjustment of the connectivity weights within neuronal ensembles in mouse primary visual cortex similarly to the cat V1.

Interplay of orientation selectivity and the power of low- and high-gamma bands in the cat primary visual cortex.

Gamma oscillations are ubiquitous in brain and are believed to be inevitable for information processing in brain. Here, we report that distinct bands (low, 30-40Hz and high gamma, 60-80Hz) of stimulus-triggered gamma oscillations are systematically linked to the orientation selectivity index (OSI) of neurons in the cat primary visual cortex. The gamma-power is high for the highly selective neurons in the low-gamma band, whereas it is high for the broadly selective neurons in the high-gamma band. We suggest that the low-gamma band is principally implicated in feed-forward excitatory flow, whereas the high-gamma band governs the flow of this excitation.

High noise correlation between the functionally connected neurons in emergent V1 microcircuits.

Neural correlations (noise correlations and cross-correlograms) are widely studied to infer functional connectivity between neurons. High noise correlations between neurons have been reported to increase the encoding accuracy of a neuronal population; however, low noise correlations have also been documented to play a critical role in cortical microcircuits. Therefore, the role of noise correlations in neural encoding is highly debated. To this aim, through multi-electrodes, we recorded neuronal ensembles in the primary visual cortex of anaesthetized cats. By computing cross-correlograms, we divulged the functional network (microcircuit) between neurons within an ensemble in relation to a specific orientation. We show that functionally connected neurons systematically exhibit higher noise correlations than functionally unconnected neurons in a microcircuit that is activated in response to a particular orientation. Furthermore, the mean strength of noise correlations for the connected neurons increases steeply than the unconnected neurons as a function of the resolution window used to calculate noise correlations. We suggest that neurons that display high noise correlations in emergent microcircuits feature functional connections which are inevitable for information encoding in the primary visual cortex.

Network-selectivity and stimulus-discrimination in the primary visual cortex: cell-assembly dynamics.

Visual neurons coordinate their responses in relation to the stimulus; however, the complex interplay between a stimulus and the functional dynamics of an assembly still eludes neuroscientists. To this aim, we recorded cell assemblies from multi-electrodes in the primary visual cortex of anaesthetized cats in response to randomly presented sine-wave drifting gratings whose orientation tilted in 22.5° steps. Cross-correlograms revealed the functional connections at all the tested orientations. We show that a cell-assembly discriminates between orientations by recruiting a 'salient' functional network at every presented orientation, wherein the connections and their strengths (peak-probabilities in the cross-correlogram) change from one orientation to another. Within these assemblies, closely tuned neurons exhibited increased connectivity and connection-strengths compared with differently tuned neurons. Minimal connectivity between untuned neurons suggests the significance of neuronal selectivity in assemblies. This study reflects upon the dynamics of functional connectivity, and brings to the fore the importance of a 'signature' functional network in an assembly that is strictly related to a specific stimulus. It appears that an assembly is the major 'functional unit' of information processing in cortical circuits, rather than the individual neurons.

Summation of connectivity strengths in the visual cortex reveals stability of neuronal microcircuits after plasticity.

BACKGROUND: Within sensory systems, neurons are continuously affected by environmental stimulation. Recently, we showed that, on cell-pair basis, visual adaptation modulates the connectivity strength between similarly tuned neurons to orientation and we suggested that, on a larger scale, the connectivity strength between neurons forming sub-networks could be maintained after adaptation-induced-plasticity. In the present paper, based on the summation of the connectivity strengths, we sought to examine how, within cell-assemblies, functional connectivity is regulated during an exposure-based adaptation. RESULTS: Using intrinsic optical imaging combined with electrophysiological recordings following the reconfiguration of the maps of the primary visual cortex by long stimulus exposure, we found that within functionally connected cells, the summed connectivity strengths remain almost equal although connections among individual pairs are modified. Neuronal selectivity appears to be strongly associated with neuronal connectivity in a "homeodynamic" manner which maintains the stability of cortical functional relationships after experience-dependent plasticity. CONCLUSIONS: Our results support the "homeostatic plasticity concept" giving new perspectives on how the summation in visual cortex leads to the stability within labile neuronal ensembles, depending on the newly acquired properties by neurons.