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

Abstract

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.

Sound induces change in orientation preference of V1 neurons: Audio-visual cross-influence

“…Shifts in the orientation tuning curves are ascribed to a decrease of responses to preferred orientation and simultaneously an increase to non-preferred orientation, that is, a push-pull mechanism. Similar shifts in orientation selectivity were reported when the adapting stimuli were visual in many species (Dragoi et al, 2000;Ghisovan et al, 2008;2009;Jeyabalaratnam et al, 2013;Chanauria et al, 2016).…”

The speed of neuronal adaptation: A perspective through the visual cortex

“…As has been modelled by King and Crowder (), such broader tuning curves and the absence of pinwheel centres in mice cortex may lead to both attractive and repulsive shifts. In addition, the effects of adaptation (whether short or long) may even extend to different layers of the cortex as has been demonstrated by Chanauria and colleagues (Chanauria et al., )—that is, layers 2–3 and 5–6 of the primary visual cortex displayed mainly attractive shifts after adaptation, suggesting that such mechanisms may be underlying principles of learning and adaptation at different cortical layers and even areas. Furthermore, within visual microcircuits, pyramidal cells on average show larger shifts of neuronal selectivity than interneurons in response to adaptation (Bachatene, Bharmauria, Rouat, & Molotchnikoff, ) wherein pyramidal cells tune the initial selectivity and interneurons regulate this selectivity.…”

Beyond differences in means: robust graphical methods to compare two groups in neuroscience

“…B. Data from Figure 5A of (Chanauria et al, 2016). C. Data from Figure 9A of (Talebi & Baker, 2016).…”

“…Figure 4 show other examples of asymmetric effects in skewed distributions. Both panels show results from recordings from the cat visual cortex from two research groups (Chanauria et al, 2016;Talebi & Baker, 2016). Panel B illustrates the adaptation response (amplitude of shift) of two independent groups of neurones with opposite responses (attractive vs. repulsive adaptation).…”