scholarly journals V1 microcircuit dynamics: altered signal propagation suggests intracortical origins for adaptation in response to visual repetition

2019 ◽  
Vol 121 (5) ◽  
pp. 1938-1952 ◽  
Author(s):  
Jacob A. Westerberg ◽  
Michele A. Cox ◽  
Kacie Dougherty ◽  
Alexander Maier
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Sensory Processing ◽  
Visual Stimulation ◽  
Current Source ◽  
Signal Propagation ◽  
Altered State ◽  
Cortical Circuits ◽  
Neuronal Interactions ◽  
Sensory Activation

Repetitive visual stimulation profoundly changes sensory processing in the primary visual cortex (V1). We show how the associated adaptive changes are linked to an altered flow of synaptic activation across the V1 laminar microcircuit. Using repeated visual stimulation, we recorded layer-specific responses in V1 of two fixating monkeys. We found that repetition-related spiking suppression was most pronounced outside granular V1 layers that receive the main retinogeniculate input. This repetition-related response suppression was robust to alternating stimuli between the eyes, in line with the notion that repetition-related adaptation is predominantly of cortical origin. Most importantly, current source density (CSD) analysis, which provides an estimate of local net depolarization, revealed that synaptic processing during repeated stimulation was most profoundly affected within supragranular layers, which harbor the bulk of cortico-cortical connections. Direct comparison of the temporal evolution of laminar CSD and spiking activity showed that stimulus repetition first affected supragranular synaptic currents, which translated into a reduction of stimulus-evoked spiking across layers. Together, these results suggest that repetition induces an altered state of intracortical processing that underpins visual adaptation. NEW & NOTEWORTHY Our survival depends on our brains rapidly adapting to ever changing environments. A well-studied form of adaptation occurs whenever we encounter the same or similar stimuli repeatedly. We show that this repetition-related adaptation is supported by systematic changes in the flow of sensory activation across the laminar cortical microcircuitry of primary visual cortex. These results demonstrate how adaptation impacts neuronal interactions across cortical circuits.

scholarly journals Functional selectivity and specific connectivity of inhibitory neurons in primary visual cortex

2018 ◽  
Author(s):  
Petr Znamenskiy ◽  
Mean-Hwan Kim ◽  
Dylan R. Muir ◽  
Maria Florencia Iacaruso ◽  
Sonja B. Hofer ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Pyramidal Cells ◽  
Fine Tuning ◽  
Inhibitory Neurons ◽  
Local Network ◽  
Cortical Circuits ◽  
Sensory Stimuli ◽  
Excitatory Neurons ◽  
Strong Excitation

In the cerebral cortex, the interaction of excitatory and inhibitory synaptic inputs shapes the responses of neurons to sensory stimuli, stabilizes network dynamics1 and improves the efficiency and robustness of the neural code2–4. Excitatory neurons receive inhibitory inputs that track excitation5–8. However, how this co-tuning of excitation and inhibition is achieved by cortical circuits is unclear, since inhibitory interneurons are thought to pool the inputs of nearby excitatory cells and provide them with non-specific inhibition proportional to the activity of the local network9–13. Here we show that although parvalbumin-expressing (PV) inhibitory cells in mouse primary visual cortex make connections with the majority of nearby pyramidal cells, the strength of their synaptic connections is structured according to the similarity of the cells’ responses. Individual PV cells strongly inhibit those pyramidal cells that provide them with strong excitation and share their visual selectivity. This fine-tuning of synaptic weights supports co-tuning of inhibitory and excitatory inputs onto individual pyramidal cells despite dense connectivity between inhibitory and excitatory neurons. Our results indicate that individual PV cells are preferentially integrated into subnetworks of inter-connected, co-tuned pyramidal cells, stabilising their recurrent dynamics. Conversely, weak but dense inhibitory connectivity between subnetworks is sufficient to support competition between them, de-correlating their output. We suggest that the history and structure of correlated firing adjusts the weights of both inhibitory and excitatory connections, supporting stable amplification and selective recruitment of cortical subnetworks.

scholarly journals A machine-learning algorithm correctly classifies cortical evoked potentials from both natural retinal stimulation and electrical stimulation of the optic nerve

2021 ◽  
Author(s):  
Vivien Gaillet ◽  
Elodie Geneviève Zollinger ◽  
Diego Ghezzi
Keyword(s):  
Electrical Stimulation ◽  
Visual Cortex ◽  
Optic Nerve ◽  
Visual Field ◽  
Primary Visual Cortex ◽  
Nerve Stimulation ◽  
Visual Stimulation ◽  
Cortical Activity ◽  
Artificial Vision ◽  
Optic Nerve Stimulation

AbstractObjectiveOptic nerve’s intraneural stimulation is an emerging neuroprosthetic approach to provide artificial vision to totally blind patients. An open question is the possibility to evoke individual non-overlapping phosphenes via selective intraneural optic nerve stimulation. To begin answering this question, first, we aim at showing in preclinical experiments with animals that each intraneural electrode could evoke a distinguishable activity pattern in the primary visual cortex.ApproachWe performed both patterned visual stimulation and patterned electrical stimulation in healthy rabbits while recording evoked cortical activity with an electrocorticogram array in the primary visual cortex. Electrical stimulation was delivered to the optic nerve with the intraneural array OpticSELINE. We used a support vector machine algorithm paired to a linear regression model to classify cortical responses originating from visual stimuli located in different portions of the visual field and electrical stimuli from the different electrodes of the OpticSELINE.Main resultsCortical activity induced by visual and electrical stimulation could be classified with nearly 100% accuracy relative to the specific location in the visual field or electrode in the array from which it originated. For visual stimulation, the accuracy increased with the separation of the stimuli and reached 100% for separation higher than 7 degrees. For electrical stimulation, at low current amplitudes, the accuracy increased with the distance between electrodes, while at higher current amplitudes, the accuracy was nearly 100% already for the shortest separation.SignificanceOptic nerve’s intraneural stimulation with the OpticSELINE induced discernible cortical activity patterns. These results represent a leap forward for intraneural optic nerve stimulation towards artificial vision.

scholarly journals Cortical subnetworks encode context of visual stimulus

2018 ◽  
Author(s):  
Jordan P. Hamm ◽  
Yuriy Shymkiv ◽  
Shuting Han ◽  
Weijian Yang ◽  
Rafael Yuste
Keyword(s):  
Visual Cortex ◽  
Visual Stimulus ◽  
Sensory Processing ◽  
Calcium Imaging ◽  
Cortical Circuits ◽  
Fundamental Function ◽  
Stimulus Context ◽  
Contextual Modulation ◽  
Two Photon ◽  
Cortical Responses

AbstractCortical processing of sensory events is significantly influenced by context. For instance, a repetitive or redundant visual stimulus elicits attenuated cortical responses, but if the same stimulus is unexpected or “deviant”, responses are augmented. This contextual modulation of sensory processing is likely a fundamental function of neural circuits, yet an understanding of how it is computed is still missing. Using holographic two-photon calcium imaging in awake animals, here we identify three distinct, spatially intermixed ensembles of neurons in mouse primary visual cortex which differentially respond to the same stimulus under separate contexts, including a subnetwork which selectively responds to deviant events. These non-overlapping ensembles are distributed across layers 2-5, though deviance detection is more common in superficial layers. Contextual preferences likely arise locally since they are not present in bottom up inputs from the thalamus or top-down inputs from prefrontal cortex. The functional parcellation of cortical circuits into independent ensembles that encode stimulus context provides a circuit basis underlying cortically based perception of novel or redundant stimuli, a key deficit in many psychiatric disorders.One Sentence SummaryVisual cortex represents deviant and redundant stimuli with separate subnetworks.

scholarly journals Magnitude, time course, and specificity of rapid adaptation across mouse visual areas

2020 ◽  
Vol 124 (1) ◽  
pp. 245-258 ◽  
Author(s):  
Miaomiao Jin ◽  
Lindsey L. Glickfeld
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Primary Visual Cortex ◽  
Sensory Processing ◽  
Time Course ◽  
Recent Experience ◽  
Rapid Adaptation ◽  
It Impacts ◽  
Visual Areas ◽  
Higher Visual Areas

Rapid adaptation dynamically alters sensory signals to account for recent experience. To understand how adaptation affects sensory processing and perception, we must determine how it impacts the diverse set of cortical and subcortical areas along the hierarchy of the mouse visual system. We find that rapid adaptation strongly impacts neurons in primary visual cortex, the higher visual areas, and the colliculus, consistent with its profound effects on behavior.

scholarly journals Orientation Tuning of Input Conductance, Excitation, and Inhibition in Cat Primary Visual Cortex

2000 ◽  
Vol 84 (2) ◽  
pp. 909-926 ◽  
Author(s):  
Jeffrey S. Anderson ◽  
Matteo Carandini ◽  
David Ferster
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Stimulation ◽  
Gain Control ◽  
Orientation Tuning ◽  
Visual Responses ◽  
Stimulus Contrast ◽  
Simple Cells ◽  
Conductance Changes ◽  
Input Conductance

The input conductance of cells in the cat primary visual cortex (V1) has been shown recently to grow substantially during visual stimulation. Because increasing conductance can have a divisive effect on the synaptic input, theoretical proposals have ascribed to it specific functions. According to the veto model, conductance increases would serve to sharpen orientation tuning by increasing most at off-optimal orientations. According to the normalization model, conductance increases would control the cell's gain, by being independent of stimulus orientation and by growing with stimulus contrast. We set out to test these proposals and to determine the visual properties and possible synaptic origin of the conductance increases. We recorded the membrane potential of cat V1 cells while injecting steady currents and presenting drifting grating patterns of varying contrast and orientation. Input conductance grew with stimulus contrast by 20–300%, generally more in simple cells (40–300%) than in complex cells (20–120%), and in simple cells was strongly modulated in time. Conductance was invariably maximal for stimuli of the preferred orientation. Thus conductance changes contribute to a gain control mechanism, but the strength of this gain control does not depend uniquely on contrast. By assuming that the conductance changes are entirely synaptic, we further derived the excitatory and inhibitory synaptic conductances underlying the visual responses. In simple cells, these conductances were often arranged in push-pull: excitation increased when inhibition decreased and vice versa. Excitation and inhibition had similar preferred orientations and did not appear to differ in tuning width, suggesting that the intracortical synaptic inputs to simple cells of cat V1 originate from cells with similar orientation tuning. This finding is at odds with models where orientation tuning in simple cells is achieved by inhibition at off-optimal orientations or sharpened by inhibition that is more broadly tuned than excitation.

Antidromic latency of magnocellular, parvocellular, and koniocellular (Blue-ON) geniculocortical relay cells in marmosets

2014 ◽  
Vol 31 (3) ◽  
pp. 263-273 ◽  
Author(s):  
SOON KEEN CHEONG ◽  
ALEXANDER NICOLAAS JOHANNES PIETERSEN
Keyword(s):  
Visual Cortex ◽  
Functional Connectivity ◽  
Primary Visual Cortex ◽  
Visual Stimulation ◽  
Blue Color ◽  
High Contrast ◽  
Response Latencies ◽  
Bon Cells ◽  
P Cells ◽  
Parallel Visual Pathways

AbstractWe studied the functional connectivity of cells in the lateral geniculate nucleus (LGN) with the primary visual cortex (V1) in anesthetized marmosets (Callithrix jacchus). The LGN sends signals to V1 along parallel visual pathways called parvocellular (P), magnocellular (M), and koniocellular (K). To better understand how these pathways provide inputs to V1, we antidromically activated relay cells in the LGN by electrically stimulating V1 and measuring the conduction latencies of P (n = 7), M (n = 14), and the “Blue-ON” (n = 5) subgroup of K cells (K-BON cells). We found that the antidromic latencies of K-BON cells were similar to those of P cells. We also measured the response latencies to high contrast visual stimuli for a subset of cells. We found the LGN cells that have the shortest latency of response to visual stimulation also have the shortest antidromic latencies. We conclude that Blue color signals are transmitted directly to V1 from the LGN by K-BON cells.

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