Complementary Codes for Odor Identity and Intensity in Olfactory Cortex

2021-11-17T10:13:44+00:00

This week on Journal Club session Shavika Rastogi will talk about a paper "Complementary Codes for Odor Identity and Intensity in Olfactory Cortex".

The ability to represent both stimulus identity and intensity is fundamental for perception. Using large-scale population recordings in awake mice, we find distinct coding strategies facilitate non- interfering representations of odor identity and intensity in piriform cortex. Simply knowing which neurons were activated is sufficient to accurately represent odor identity, with no additional information about identity provided by spike time or spike count. Decoding analyses indicate that cortical odor representations are not sparse. Odorant concentration had no systematic effect on spike counts, indicating that rate cannot encode intensity. Instead, odor intensity can be encoded by temporal features of the population response. We found a subpopulation of rapid, largely concentration-invariant responses was followed by another population of responses whose latencies systematically decreased at higher concentrations. Cortical inhibition transforms olfactory bulb output to sharpen these dynamics. Our data therefore reveal complementary coding strategies that can selectively represent distinct features of a stimulus.

Papers:

K. Bolding, K. Franks, "Complementary Codes for Odor Identity and Intensity in Olfactory Cortex", 2017, eLife, 6, e22630

Date: 2021/11/19
Time: 14:00
Location: online

Bursting Neurons Signal Input Slope

2021-04-21T11:37:00+01:00

This week on Journal Club session Volker Steuber will talk about a paper "Bursting Neurons Signal Input Slope".

Brief bursts of high-frequency action potentials represent a common firing mode of pyramidal neurons, and there are indications that they represent a special neural code. It is therefore of interest to determine whether there are particular spatial and temporal features of neuronal inputs that trigger bursts. Recent work on pyramidal cells indicates that bursts can be initiated by a specific spatial arrangement of inputs in which there is coincident proximal and distal dendritic excitation (Larkum et al., 1999). Here we have used a computational model of an important class of bursting neurons to investigate whether there are special temporal features of inputs that trigger bursts. We find that when a model pyramidal neuron receives sinusoidally or randomly varying inputs, bursts occur preferentially on the positive slope of the input signal. We further find that the number of spikes per burst can signal the magnitude of the slope in a graded manner. We show how these computations can be understood in terms of the biophysical mechanism of burst generation. There are several examples in the literature suggesting that bursts indeed occur preferentially on positive slopes (Guido et al., 1992; Gabbiani et al., 1996). Our results suggest that this selectivity could be a simple consequence of the biophysics of burst generation. Our observations also raise the possibility that neurons use a burst duration code useful for rapid information transmission. This possibility could be further examined experimentally by looking for correlations between burst duration and stimulus variables.

Papers:

A. Kepecs, X. Wang, J. Lisman, "Bursting Neurons Signal Input Slope", 2002, The Journal of Neuroscience, 22, 9053--9062

Date: 2021/04/23
Time: 14:00
Location: online

UH Biocomputation Group - Neural coding

Complementary Codes for Odor Identity and Intensity in Olfactory Cortex

Bursting Neurons Signal Input Slope