Biology subjects

Chauhan, T.

Publications and source records attributed to Chauhan, T..

7 recordsLinked to original sources

bioRxiv2024

CHARACTERISING REPRESENTATIONS OF HUE AND SATURATION IN THE CORTEX USING INFORMATION DECODING

One of the enduring questions in the field of colour vision research revolves around how features of colour appearance, such as hue and saturation are represented in the brain. While considerable progress has been made in understanding the transformation of physical colour signals during early processing stages, the mechanisms by which these signals are recombined in later processing, ultimately giving rise to our perceptual experience of colour, remain elusive. A promising avenue for capturing these representations involves decoding from EEG signals. We captured EEG signals in response to 8 evenly spaced isoluminant colours at two saturation levels, taken from a perceptually uniform CIE Lab colour space. Surprisingly, our main finding challenges the expectation that representations of colours that are perceptually more similar elicit more similar signals. Instead, our results show that isoluminant hues perceived as maximally dissimilar tend to evoke the most similar EEG signals, which is in line with predictions derived from opponent theory. Additionally, decoding performs better for lower saturation than for higher saturation hues, contrary to expectations that more distinct hue representations would be associated with highly saturated hues but in line with prediction of magnified differences in latency and amplitude of EEG signals between low-level opponent mechanisms at lower contrast levels. Finally, our findings also highlight the non- uniformity of the cortical representation space for isoluminant colour, indicating that neighbouring hues exhibit varying degrees of similarity. Put together, the results show that low-level features, such as contrast and cone-opponency, drive the EEG response to colour.

neuroscience↗

bioRxiv2021

Decoding of EEG signals reveals non-uniformities in the neural geometry of colour

The idea of colour opponency maintains that colour vision arises through the comparison of two chromatic mechanisms, red versus green (RG) and yellow versus blue (YB). The four unique hues, red, green, blue, and yellow, are assumed to appear at the null points of these the two chromatic systems. However, whether unique hues have a distinct signature that can be reliably discerned in neural activity is still an open question. Here we hypothesise that, if unique hues represent a tractable cortical state, they should elicit more robust activity compared to non-unique hues. We use a spatiotemporal decoding approach to reconstruct an activation space for a set of unique and intermediate hues across a range of luminance values. We show that electroencephalographic (EEG) responses carry robust information about isoluminant unique hues within a 100-300 ms window from stimulus onset. Decoding is possible in both passive and active viewing tasks, but is compromised when concurrent high luminance contrast is added to the colour signals. The efficiency of hue decoding is not entirely predicted by their mutual distance in a nominally uniform perceptual colour space. Instead, the encoding space shows pivotal non-uniformities which suggest that anisotropies in neurometric hue-spaces are likely to represent perceptual unique hues. Furthermore, the neural code for hue temporally coincides with the neural code for luminance contrast, thus explaining why potential neural correlates of unique hues have remained so elusive until now.

neuroscience↗

bioRxiv2021

Supramolecular cylinders target bulge structures in the 5-prime UTR of the RNA genome of SARS-CoV-2 and inhibit viral replication

The untranslated regions (UTRs) of viral genomes contain a variety of conserved yet dynamic structures crucial for viral replication, providing drug targets for the development of broad spectrum anti-virals. We combine in vitro RNA analysis with Molecular Dynamics simulations to build the first 3D models of the structure and dynamics of key regions of the 5 UTR of the SARS-CoV-2 genome. Furthermore, we determine the binding of metallo-supramolecular helicates (cylinders) to this RNA structure. These nano-size agents are uniquely able to thread through RNA junctions and we identify their binding to a 3-base bulge and the central cross 4-way junction located in the stem loop 5. Finally, we show these RNA-binding cylinders suppress SARS-CoV-2 replication, highlighting their potential as novel antiviral agents.

biochemistry↗

bioRxiv2020

Simultaneous mental updating in physical space and number space

People can track moving objects after they disappear or become occluded. For instance, they can estimate the position of a car after it goes behind a truck. People can also track through feature space after occlusion. For instance, they can estimate the current number on a hidden stopwatch. Previous work has suggest that a common rate control module paces mental updating in both physical space and number-space. We tested this by comparing single and dual task conditions. On every trial, participants observed a moving target-counter travel clockwise round a circular track. In the then disappeared for 2, 4, 6 or 8 seconds, and beep sounded. In the single task blocks, participants either estimated the final position or the final number. In the dual task block, they estimated final position and final number. Performance was very similar in single and dual task blocks. This suggests people can extrapolate through physical space and number space simultaneously. This is a challenge to the common rate control model, which implies there should be some dual task interference. We conclude that if a common rate controller exists, it is capable of pacing simultaneous mental simulations in different dimensions.

neuroscience↗

bioRxiv2019

Sub-optimality of the early visual system explained through biologically plausible plasticity

The early visual cortex is the site of crucial pre-processing for more complex, biologically relevant computations that drive perception and, ultimately, behaviour. This pre-processing is often viewed as an optimisation which enables the most efficient representation of visual input. However, measurements in monkey and cat suggest that receptive fields in the primary visual cortex are often noisy, blobby, and symmetrical, making them sub-optimal for operations such as edge-detection. We propose that this suboptimality occurs because the receptive fields do not emerge through a global minimisation of the generative error, but through locally operating biological mechanisms such as spike-timing dependent plasticity. Using an orientation discrimination paradigm, we show that while sub-optimal, such models offer a much better description of biology at multiple levels: single-cell, population coding, and perception. Taken together, our results underline the need to carefully consider the distinction between information-theoretic and biological notions of optimality in early sensorial populations.

systems biology↗

bioRxiv2019

Stimulation-specific information is represented as local activity patterns across the brain

Modern neuroimaging represents three-dimensional brain activity, which varies across brain regions. It remains unknown whether activity within brain regions is organized in spatial configurations to reflect perceptual and cognitive processes. We developed a rotational cross-correlation method allowing a straightforward analysis of spatial activity patterns for the precise detection of the spatially correlated distributions of brain activity. Using several statistical approaches, we found that the seed patterns in the fusiform face area were robustly correlated to brain regions involved in face-specific representations. These regions differed from the non-specific visual network meaning that activity structure in the brain is locally preserved in stimulation-specific regions. Our findings indicate spatially correlated perceptual representations in cerebral activity and suggest that the 3D coding of the processed information is organized in locally preserved activity patterns. More generally, our results provide the first demonstration that information is represented and transmitted as local spatial configurations of brain activity.

neuroscience↗

bioRxiv2017

Emergence of binocular disparity selectivity through Hebbian learning

Neural selectivity in the early visual cortex strongly reflects the statistics of our environment (Barlow, 2001; Geisler, 2008). Although this has been described extensively in literature through various encoding hypotheses (Barlow and Foldiak, 1989; Atick and Redlich, 1992; Olshausen and Field, 1996), an explanation as to how the cortex develops the structures to support these encoding schemes remains elusive. Here, using the more realistic example of binocular vision as opposed to monocular luminance-field images, we show how a simple Hebbian coincidence-detector is capable of accounting for the emergence of binocular, disparity selective, receptive fields. We propose a model based on spike-timing dependent plasticity (STDP) which not only converges to realistic single-cell and population characteristics, but also demonstrates how known biases in natural statistics may influence population encoding and downstream correlates of behaviour. Furthermore, we show that the receptive fields we obtain are closer in structure to electrophysiological data than those predicted by normative encoding schemes (Ringach, 2002). We also demonstrate the robustness of our model to the input dataset, noise at various processing stages, and internal parameter variation. Taken together, our modelling results suggest that Hebbian coincidence-detection is an important computational principle and could provide a biologically plausible mechanism for the emergence of selectivity to natural statistics in the early sensory cortex.

neuroscience↗