Decoding

Decoding

Owing to the well-studied feed-forward anatomy, the thalamus is classically described as a relay station between the sensory periphery and the cortex. However, the complex dynamic interaction between the thalamic and cortical structures is perhaps the key element in establishing representations that ultimately result in perception of our sensory environment. In these projects, we quantify information transmission in the thalamocortical pathway under varying stimulation conditions and sensory modalities.

Information transmission in the vibrissa pathway

TC_fig1Given the sensitivity of the thalamocortical synapse to closely timed spikes and the importance of fine timing precision for the faithful representation of sensory information, the modulation of thalamic population timing over these time scales is likely important for cortical representations of the dynamic natural sensory environment. The canonical network architecture of the thalamocortical circuit, along with the extensive literature on the discretized anatomy of the rodent vibrissa system, makes this an ideal model system for studying the transmission of information in the thalamocortical circuit.

Using this pathway, we show that sensory adaptation differentially influences thalamic and cortical activity in a manner that fundamentally changes the nature of the information conveyed about the sensory input. Specifically, from the perspective of an ideal observer of spiking activity, the cortical neurons show a degraded performance in detecting vibrissal deflections with adaptation, while showing an enhancement in discriminating between deflections of different velocities. Analysis of simultaneously recorded thalamic neurons did unveil, however, an analogous adaptive change in thalamic synchrony that mirrors the observations of cortical response magnitude. The results here suggest an adaptive shift in the coding strategy that has direct functional consequences regarding the nature of information relayed to cortex.

Q. Wang, R. M. Webber, and G. B. Stanley. Thalamic synchrony and the adaptive gating of information flow to cortex, Nature Neuroscience, 13(12):1534-1541, 2010. PDF, Supplement

D. R. Ollerenshaw, H. J. V. Zheng, Q. Wang, and G. B. Stanley, The adaptive trade-off between detection and discrimination in cortical representations and behavior, Neuron., Mar 5;81(5):1152-64, 2014. PDF

He J. V. Zheng, Qi Wang, & Garrett B. Stanley, Adaptive Shaping of Cortical Response Selectivity in the Vibrissa Pathway,  J Neurophysiol, 2015. PDF

Probabilistic Coding and Cortical Variability

CaptureIt is unclear how reliable and stable perceptions are coded when neural representations are noisy and at times, inconsistent.  Our group uses the rodent barrel cortex is a model of somatosensation.  Using voltage sensitive dye imaging of the barrel cortex, we observed that population responses were unreliable in response to whisker deflections of different velocities in an anesthetized animal. We hypothesis that these representations are more than just variable, they are in fact probabilistic responses. Given this observation, we hypothesize that whiskers can as unreliable detectors of a stimulus and that altering the response probability can modulate perceptional experiences. In the future, both theoretical and experimental work will be used to determine both the mechanism of these representations and investigate if these probabilistic response dynamics exist in the awake brain

Clare Gollnick, Daniel Millard, Alexander Ortiz, Ravi Bellamkonda, and Garrett Stanley, “Reliability and the Neural Code: The Probability of Activation Hypothesis”, submitted 2015

Population Representation of Natural Scenes in the visual pathway

hallway

Neural codes don’t just encompass how single neurons represent information, they also describe how entire populations of neurons represent information. Nowhere is this more apparent than in the visual system where the outside world contains infinite scenes that change on a very fine spatial scale. Understanding how populations of neurons collectively capture this complexity is key to understanding sensory information transmission.

To investigate the way populations encode natural scenes, we use a stimulus that we built from hand to simulate natural features while still employing strong excitation. We call this the sinusoidal hallway as it mirrors the phenomena observed when walking through a hallway but uses sinusoidal textures as a wallpaper. This stimulus contains both motion boundaries – areas where different types of motion meet – and spatially varying spatial frequencies. Of interest in this stimulus is both determining how this (and other) naturalistic stimuli are encoded in primary visual cortex and how we can use recorded responses from primary visual cortex to decode these stimuli. Preliminary results indicate that there are interesting relationships between the presence of natural features and how well classical models of neural encoding perform and yet decoding remains relatively consistently accurate. It appears that decoding uses the population to multiply sample the space and provide increased accuracy.

S. T. Kelly, J. Kremkow, J. Jin, Y. Wang, Q. Wang, J. M. Alonso, G. B. Stanley. The Role of Thalamic Population Synchrony In the Emergence of Cortical Feature Selectivity, PLoS Comput Biol., Jan;10(1):e1003418, 2014.PDF