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

KETAMINE: Neural- and network-level changes

Ketamine is a widely used clinical drug that has several functional and clinical applications, including its use as an anaesthetic, analgesic, anti-depressive, anti-suicidal agent, among others. Among its diverse behavioral effects, it influences short-term memory and induces psychedelic effects. At the neural level across different brain areas, it modulates neural firing rates, neural tuning, brain oscillations, and modularity, while promoting hypersynchrony and random connectivity between neurons. In our recent studies we demonstrated that topical application of ketamine on the visual cortex alters neural tuning and promotes vigorous connectivity between neurons by decreasing their firing variability. Here, we begin with a brief review of the literature, followed by results from our lab, where we synthesize a dendritic model of neural tuning and network changes following ketamine application. This model has potential implications for focused modulation of cortical networks in clinical settings. Finally, we identify current gaps in research and suggest directions for future studies, particularly emphasizing the need for more animal experiments to establish a platform for effective translation and synergistic therapies combining ketamine with other protocols such as training and adaptation. In summary, investigating ketamine's broader systemic effects, not only provides deeper insight into cognitive functions and consciousness but also paves the way to advance therapies for neuropsychiatric disorders.

Multiunit Frontal Eye Field Activity Codes the Visuomotor Transformation, But Not Gaze Prediction or Retrospective Target Memory, in a Delayed Saccade Task

Single-unit (SU) activity-action potentials isolated from one neuron-has traditionally been employed to relate neuronal activity to behavior. However, recent investigations have shown that multiunit (MU) activity-ensemble neural activity recorded within the vicinity of one microelectrode-may also contain accurate estimations of task-related neural population dynamics. Here, using an established model-fitting approach, we compared the spatial codes of SU response fields with corresponding MU response fields recorded from the frontal eye fields (FEFs) in head-unrestrained monkeys (Macaca mulatta) during a memory-guided saccade task. Overall, both SU and MU populations showed a simple visuomotor transformation: the visual response coded target-in-eye coordinates, transitioning progressively during the delay toward a future gaze-in-eye code in the saccade motor response. However, the SU population showed additional secondary codes, including a predictive gaze code in the visual response and retention of a target code in the motor response. Further, when SUs were separated into regular/fast spiking neurons, these cell types showed different spatial code progressions during the late delay period, only converging toward gaze coding during the final saccade motor response. Finally, reconstructing MU populations (by summing SU data within the same sites) failed to replicate either the SU or MU pattern. These results confirm the theoretical and practical potential of MU activity recordings as a biomarker for fundamental sensorimotor transformations (e.g., target-to-gaze coding in the oculomotor system), while also highlighting the importance of SU activity for coding more subtle (e.g., predictive/memory) aspects of sensorimotor behavior.

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.

The effects of distractors on brightness perception based on a spiking network

Visual perception can be modified by the surrounding context. Particularly, experimental observations have demonstrated that visual perception and primary visual cortical responses could be modified by properties of surrounding distractors. However, the underlying mechanism remains unclear. To simulate primary visual cortical activities in this paper, we design a k-winner-take-all (k-WTA) spiking network whose responses are generated through probabilistic inference. In simulations, images with the same target and various surrounding distractors perform as stimuli. Distractors are designed with multiple varying properties, including the luminance, the sizes and the distances to the target. Simulations for each varying property are performed with other properties fixed. Each property could modify second-layer neural responses and interactions in the network. To the same target in the designed images, the modified network responses could simulate distinguishing brightness perception consistent with experimental observations. Our model provides a possible explanation of how the surrounding distractors modify primary visual cortical responses to induce various brightness perception of the given target.

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.

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.

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.

Coordinated neuronal ensembles in primary auditory cortical columns

The synchronous activity of groups of neurons is increasingly thought to be important in cortical information processing and transmission. However, most studies of processing in the primary auditory cortex (AI) have viewed neurons as independent filters; little is known about how coordinated AI neuronal activity is expressed throughout cortical columns and how it might enhance the processing of auditory information. To address this, we recorded from populations of neurons in AI cortical columns of anesthetized rats and, using dimensionality reduction techniques, identified multiple coordinated neuronal ensembles (cNEs), which are groups of neurons with reliable synchronous activity. We show that cNEs reflect local network configurations with enhanced information encoding properties that cannot be accounted for by stimulus-driven synchronization alone. Furthermore, similar cNEs were identified in both spontaneous and evoked activity, indicating that columnar cNEs are stable functional constructs that may represent principal units of information processing in AI.

Information and the Origin of Qualia

This article argues that qualia are a likely outcome of the processing of information in local cortical networks. It uses an information-based approach and makes a distinction between information structures (the physical embodiment of information in the brain, primarily patterns of action potentials), and information messages (the meaning of those structures to the brain, and the basis of qualia). It develops formal relationships between these two kinds of information, showing how information structures can represent messages, and how information messages can be identified from structures. The article applies this perspective to basic processing in cortical networks or ensembles, showing how networks can transform between the two kinds of information. The article argues that an input pattern of firing is identified by a network as an information message, and that the output pattern of firing generated is a representation of that message. If a network is encouraged to develop an attractor state through attention or other re-entrant processes, then the message identified each time physical information is cycled through the network becomes “representation of the previous message”. Using an example of olfactory perception, it is shown how this piggy-backing of messages on top of previous messages could lead to olfactory qualia. The message identified on each pass of information could evolve from inner identity, to inner form, to inner likeness or image. The outcome is an olfactory quale. It is shown that the same outcome could result from information cycled through a hierarchy of networks in a resonant state. The argument for qualia generation is applied to other sensory modalities, showing how, through a process of brain-wide constraint satisfaction, a particular state of consciousness could develop at any given moment. Evidence for some of the key predictions of the theory is presented, using ECoG data and studies of gamma oscillations and attractors, together with an outline of what further evidence is needed to provide support for the theory.

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.