Amplification of Trial-to-Trial Response Variability by Neurons in Visual Cortex

The visual cortex responds to repeated presentations of the same stimulus with high variability. Because the firing mechanism is remarkably noiseless, the source of this variability is thought to lie in the membrane potential fluctuations that result from summated synaptic input. Here this hypothesis is tested through measurements of membrane potential during visual stimulation. Surprisingly, trial-to-trial variability of membrane potential is found to be low. The ratio of variance to mean is much lower for membrane potential than for firing rate. The high variability of firing rate is explained by the threshold present in the function that converts inputs into firing rates. Given an input with small, constant noise, this function produces a firing rate with a large variance that grows with the mean. This model is validated on responses recorded both intracellularly and extracellularly. In neurons of visual cortex, thus, a simple deterministic mechanism amplifies the low variability of summated synaptic inputs into the large variability of firing rate. The computational advantages provided by this amplification are not known

An uncorrelated state for the cortex?

The spike trains of nearby neurons in the sensory cortex are typically thought to be correlated due to mutual connections and common input. Multiple studies have measured these correlations and found them to be substantial (in the range of 10-40%). Two recent papers, however, reported that average correlations can be an order of magnitude smaller. Such low correlations could indicate an ‘uncorrelated state’ for the cortex, where cortical neurons act independently even in the face of strong common input

Visuomotor association orthogonalizes visual cortical population codes

The brain should be best able to associate distinct behavioral responses to sensory stimuli if these stimuli evoke population firing patterns that are close to orthogonal. To investigate whether task training orthogonalizes population codes in primary visual cortex (V1), we measured the orientation tuning of 4,000-neuron populations in mouse V1 before and after training on a visuomotor task. The effect of task training on population codes could be captured by a simple mathematical transformation of firing rates, which suppressed responses to motor-associated stimuli, but only in cells responding to them at intermediate levels. This transformation orthogonalized the representations of the task orientations by sparsening the population responses to these stimuli. The strength of response transformation varied from trial to trial, suggesting a dynamic circuit mechanism rather than static synaptic plasticity. These results indicate a simple process by which visuomotor associations orthogonalize population codes as early as in primary visual cortex

Masking by fast gratings

Perception of an oriented pattern is impaired in the presence of a superimposed orthogonal mask. This masking effect most likely arises in visual cortex, where neuronal responses are suppressed by masks having a broad range of orientations. Response suppression is commonly ascribed to lateral inhibition between cortical neurons. Recent physiological results, however, have cast doubt on this view: powerful suppression has been observed with masks drifting too rapidly to elicit much of a response in cortex. We show here that the same is true for perceptual masking. From contrast discrimination thresholds, we estimated the cortical response to drifting patterns of various frequencies, and found it greatly reduced above 15-20 Hz. In the same subjects, we measured the strength of masking by the same patterns and found it equally strong for masks drifting slowly (2.7 Hz) as for masks drifting rapidly (27-38 Hz). Fast gratings thus cause strong masking while eliciting weak cortical responses. Our results might be explained by inhibition from cortical neurons that respond to unusually high frequencies, and yet do not make their signals fully available for perceptual judgments. A more parsimonious explanation, however, is that masking does not involve lateral inhibition from cortex. Masking might operate in retina or thalamus, which respond to much higher frequencies than cortex. Masking might also be due to thalamic signals to cortex, perhaps through depression at thalamocortical synapses

Fast and accurate spike sorting of high-channel count probes with KiloSort

Marius Pachitariu, Nick Steinmetz, Shabnam Kadir, Matteo Carandini, and Kenneth Harris, ‘Fast and accurate spike sorting of high-channel count probes with KiloSort’, Paper presented at the Neural Information Processing Systems (NIPS 2016) Conference, 5 -10 December 2016, Centre Convencions Internacional, Barcelona, Spain, https://papers.nips.cc/book/advances-in-neural-information-processing-systems-29-2016New silicon technology is enabling large-scale electrophysiological recordings in vivo from hundreds to thousands of channels. Interpreting these recordings requires scalable and accurate automated methods for spike sorting, which should minimize the time required for manual curation of the results. Here we introduce KiloSort, a new integrated spike sorting framework that uses template matching both during spike detection and during spike clustering. KiloSort models the electrical voltage as a sum of template waveforms triggered on the spike times, which allows overlapping spikes to be identified and resolved. Unlike previous algorithms that compress the data with PCA, KiloSort operates on the raw data which allows it to construct a more accurate model of the waveforms. Processing times are faster than in previous algorithms thanks to batch-based optimization on GPUs. We compare KiloSort to an established algorithm and show favorable performance, at much reduced processing times. A novel post-clustering merging step based on the continuity of the templates further reduced substantially the number of manual operations required on this data, for the neurons with near-zero error rates, paving the way for fully automated spike sorting of multichannel electrode recordings

Task specificity in mouse parietal cortex

Parietal cortex is implicated in a variety of behavioral processes, but it is unknown whether and how its individual neurons participate in multiple tasks. We trained head-fixed mice to perform two visual decision tasks involving a steering wheel or a virtual T-maze and recorded from the same parietal neurons during these two tasks. Neurons that were active during the T-maze task were typically inactive during the steering-wheel task and vice versa. Recording from the same neurons in the same apparatus without task stimuli yielded the same specificity as in the task, suggesting that task specificity depends on physical context. To confirm this, we trained some mice in a third task combining the steering wheel context with the visual environment of the T-maze. This hybrid task engaged the same neurons as those engaged in the steering-wheel task. Thus, participation by neurons in mouse parietal cortex is task specific, and this specificity is determined by physical context

Mouse frontal cortex mediates additive multisensory decisions

The brain can combine auditory and visual information to localize objects. However, the cortical substrates underlying audiovisual integration remain uncertain. Here, we show that mouse frontal cortex combines auditory and visual evidence; that this combination is additive, mirroring behavior; and that it evolves with learning. We trained mice in an audiovisual localization task. Inactivating frontal cortex impaired responses to either sensory modality, while inactivating visual or parietal cortex affected only visual stimuli. Recordings from >14,000 neurons indicated that after task learning, activity in the anterior part of frontal area MOs (secondary motor cortex) additively encodes visual and auditory signals, consistent with the mice's behavioral strategy. An accumulator model applied to these sensory representations reproduced the observed choices and reaction times. These results suggest that frontal cortex adapts through learning to combine evidence across sensory cortices, providing a signal that is transformed into a binary decision by a downstream accumulator

Visuomotor learning promotes visually evoked activity in the medial prefrontal cortex

The medial prefrontal cortex (mPFC) is necessary for executing many learned associations between stimuli and movement. It is unclear, however, how activity in the mPFC evolves across learning, and how this activity correlates with sensory stimuli and the learned movements they evoke. To address these questions, we record cortical activity with widefield calcium imaging while mice learned to associate a visual stimulus with a forelimb movement. After learning, the mPFC shows stimulus-evoked activity both during task performance and during passive viewing, when the stimulus evokes no action. This stimulus-evoked activity closely tracks behavioral performance across training, with both exhibiting a marked increase between days when mice first learn the task, followed by a steady increase with further training. Electrophysiological recordings localized this activity to the secondary motor and anterior cingulate cortex. We conclude that learning a visuomotor task promotes a route for visual information to reach the prefrontal cortex