Reprogramming of orientation columns in visual cortex: a domino effect

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.

Effects of visual adaptation on orientation selectivity in cat secondary visual cortex

Neuron orientation selectivity, otherwise known as the ability to respond optimally to a preferred orientation, has been extensively described in both primary and secondary visual cortices. This orientation selectivity, conserved through all cortical layers of a given column, is the primary basis for cortical organization and functional network emergence. While this selectivity is programmed and acquired since critical period, it has always been believed that in a mature brain, neurons' inherent functional features could not be changed. However, a plurality of studies has investigated the mature brain plasticity in V1, by changing the cells' orientation selectivity with visual adaptation. Using electrophysiological data in both V1 and V2 areas, this study aims to investigate the effects of adaptation on simultaneously recorded cells in both areas. Visual adaptation had an enhanced effect on V2 units, as they exhibited greater tuning curve shifts and a more pronounced decrease of their OSI. Not only did adaptation have a different effect on V2 neurons, it also elicited a different response depending on the neuron's cortical depth. Indeed, in V2, cells in layers II-III were more affected by visual adaptation, while infragranular layer V units exhibited little to no effect at all.

Shifting Developmental Trajectories During Critical Periods of Brain Formation

Critical periods of brain development are epochs of heightened plasticity driven by environmental influence necessary for normal brain function. Recent studies are beginning to shed light on the possibility that timely interventions during critical periods hold potential to reorient abnormal developmental trajectories in animal models of neurological and neuropsychiatric disorders. In this review, we re-examine the criteria defining critical periods, highlighting the recently discovered mechanisms of developmental plasticity in health and disease. In addition, we touch upon technological improvements for modeling critical periods in human-derived neural networks in vitro. These scientific advances associated with the use of developmental manipulations in the immature brain of animal models are the basic preclinical systems that will allow the future translatability of timely interventions into clinical applications for neurodevelopmental disorders such as intellectual disability, autism spectrum disorders (ASD) and schizophrenia.

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.

Forward models demonstrate that repetition suppression is best modelled by local neural scaling

Inferring neural mechanisms from functional magnetic resonance imaging (fMRI) is challenging because the fMRI signal integrates over millions of neurons. One approach is to compare computational models that map neural activity to fMRI responses, to see which best predicts fMRI data. We use this approach to compare four possible neural mechanisms of fMRI adaptation to repeated stimuli (scaling, sharpening, repulsive shifting and attractive shifting), acting across three domains (global, local and remote). Six features of fMRI repetition effects are identified, both univariate and multivariate, from two independent fMRI experiments. After searching over parameter values, only the local scaling model can simultaneously fit all data features from both experiments. Thus fMRI stimulus repetition effects are best captured by down-scaling neuronal tuning curves in proportion to the difference between the stimulus and neuronal preference. These results emphasise the importance of formal modelling for bridging neuronal and fMRI levels of investigation.

Dynamics of Stability of Orientation Maps Recorded with Optical Imaging

Orientation selectivity is an important feature of visual cortical neurons. Optical imaging of the visual cortex allows for the generation of maps of orientation selectivity that reflect the activity of large populations of neurons. To estimate the statistical significance of effects of experimental manipulations, evaluation of the stability of cortical maps over time is required. Here, we performed optical imaging recordings of the visual cortex of anesthetized adult cats. Monocular stimulation with moving clockwise square-wave gratings that continuously changed orientation and direction was used as the mapping stimulus. Recordings were repeated at various time intervals, from 15 min to 16 h. Quantification of map stability was performed on a pixel-by-pixel basis using several techniques. Map reproducibility showed clear dynamics over time. The highest degree of stability was seen in maps recorded 15-45 min apart. Averaging across all time intervals and all stimulus orientations revealed a mean shift of 2.2 ± 0.1°. There was a significant tendency for larger shifts to occur at longer time intervals. Shifts between 2.8° (mean ± 2SD) and 5° were observed more frequently at oblique orientations, while shifts greater than 5° appeared more frequently at cardinal orientations. Shifts greater than 5° occurred rarely overall (5.4% of cases) and never exceeded 11°. Shifts of 10-10.6° (0.7%) were seen occasionally at time intervals of more than 4 h. Our findings should be considered when evaluating the potential effect of experimental manipulations on orientation selectivity mapping studies.

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.

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.

Electrophysiological and firing properties of neurons: Categorizing soloists and choristers in primary visual cortex

Visual processing in the cortex involves various aspects of neuronal properties such as morphological, electrophysiological and molecular. In particular, the neural firing pattern is an important indicator of dynamic circuitry within a neuronal population. Indeed, in microcircuits, neurons act as soloists or choristers wherein the characteristical activity of a 'soloist' differs from the firing pattern of a 'chorister'. Both cell types correlate their respective firing rate with the global populational activity in a unique way. In the present study, we sought to examine the relationship between the spike shape (thin spike neurons and broad spike neurons) of cortical neurons recorded from V1, their firing levels and their propensity to act as soloists or choristers. We found that thin spike neurons, which exhibited higher levels of firing, generally correlate their activity with the neuronal population (choristers). On the other hand, broad spike neurons showed lower levels of firing and demonstrated weak correlations with the assembly (soloists). A major consequence of the present study is: estimating the correlation of neural spike trains with their neighboring population is a predictive indicator of spike waveforms and firing level. Indeed, we found a continuum distribution of coupling strength ranging from weak correlation-strength (attributed to low-firing neurons) to high correlation-strength (attributed to high-firing neurons). The tendency to exhibit high- or low-firing is conducive to the spike shape of neurons. Our results offer new insights into visual processing by showing how high-firing rate neurons (mostly thin spike neurons) could modulate the neuronal responses within cell-assemblies.