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Deneux, T.

Publications and source records attributed to Deneux, T..

3 recordsLinked to original sources

Cortical recruitment determines learning dynamics and strategy

Salience is a broad and widely used concept in neuroscience whose neuronal correlates, however, remain elusive. In behavioral conditioning, salience is used to explain various effects, such as stimulus overshadowing, and refers to how fast and strongly a stimulus can be associated with a conditioned event. Here, we show that sounds of diverse quality, but equal intensity and perceptual detectability, can recruit different levels of population activity in mouse auditory cortex. When using these sounds as cues in a Go/NoGo discrimination task, the degree of cortical recruitment matches the salience parameter of a reinforcement learning model used to analyze learning speed. We test an essential prediction of this model by training mice to discriminate light-sculpted optogenetic activity patterns in auditory cortex, and verify that cortical recruitment causally determines association or overshadowing of the stimulus components. This demonstrates that cortical recruitment underlies major aspects of stimulus salience during reinforcement learning.

neuroscience

Context-dependent signaling of coincident auditory and visual events in primary visual cortex

Detecting rapid coincident changes across sensory modalities is essential to recognize sudden threats and events. Using two-photon calcium imaging in identified cell types in awake mice, we show that auditory cortex (AC) neurons projecting to primary visual cortex (V1) preferentially encode the abrupt onsets of sounds. In V1, a sub-population of layer 1 interneurons gates this selective cross-modal information by a suppression specific to the absence of visual inputs. However, when large auditory onsets coincide with visual stimuli, visual responses are strongly boosted in V1. Thus, a dynamic asymmetric circuit across AC and V1 specifically identifies visual events starting simultaneously to sudden sounds, potentially catalyzing localization of new sound sources in the visual field.

neuroscience

Community-based benchmarking improves spike inference from two-photon calcium imaging data

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations1, 2. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators3. Different algorithms for estimating spike trains from noisy calcium measurements have been proposed in the past4-8, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.

neuroscience