Stable representation of a naturalistic movie emerges from episodic activity with gain variability

Visual cortical responses are known to be highly variable across trials within an experimental session. However, the long-term stability of visual cortical responses is poorly understood. Here using chronic imaging of V1 in mice we show that neural responses to repeated natural movie clips are unstable across weeks. Individual neuronal responses consist of sparse episodic activity which are stable in time but unstable in gain across weeks. Further, we find that the individual episode, instead of neuron, serves as the basic unit of the week-to-week fluctuation. To investigate how population activity encodes the stimulus, we extract a stable one-dimensional representation of the time in the natural movie, using an unsupervised method. Most week-to-week fluctuation is perpendicular to the stimulus encoding direction, thus leaving the stimulus representation largely unaffected. We propose that precise episodic activity with coordinated gain changes are keys to maintain a stable stimulus representation in V1.

Macaque V1 responses to 2nd-order contrast-modulated stimuli and the possible subcortical and cortical contributions

V1 neurons as linear filters supposedly only respond to 1st-order luminance-modulated (LM) stimuli, but not 2nd-order contrast-modulated (CM) ones. To solve this difficulty, filter-rectify-filter models are proposed, in which first-stage filters respond to CM stimulus elements, and the nonlinear-rectified outputs are summed by a second-stage filter for CM stimulus representation. Correspondingly, neurophysiological evidence shows V1/A17 neurons less responsive to CM stimuli than V2/A18 neurons. Here we used two-photon calcium imaging to demonstrate substantial V1 responses to CM gratings with unimodally distributed LM/CM preferences. Moreover, LM responses are suppressed by LM and CM adaptations regardless of orientation, but CM responses are more suppressed by same-orientation LM and CM adaptations than by orthogonal ones. While LM adaptation results agree with the Hubel-Wiesel view of LGN contributions to V1 orientation responses, CM adaptation results, which include both orientation-unspecific and specific components, may suggest similar subcortical contributions plus additional refinement by recurrent intracortical interactions.

Stable representation of a naturalistic movie emerges from episodic activity with gain variability

Visual cortical responses are known to be highly variable across trials within an experimental session. However, the long-term stability of visual cortical responses is poorly understood. Chronic imaging experiments in V1 showed that neural responses to repeated natural movie clips were unstable across weeks. Single neuronal responses consisted of sparse episodic activity which were stable in time but unstable in spike rates across weeks. Further, we found that the individual episode, instead of neuron, served as the basic unit of the week-to-week fluctuation. To investigate how population activity encodes the stimulus, we extracted a stable one-dimensional representation of the time in the natural movie, using an unsupervised method. Moreover, most week-to-week fluctuation was perpendicular to the stimulus encoding direction, thus leaving the stimulus representation largely unaffected. We propose that precise episodic activity with coordinated gain changes are keys to maintain a stable stimulus representation in V1.

Developmental divergence of sensory stimulus representation in cortical interneurons

Vasocative-intestinal-peptide (VIP+) and somatostatin (SST+) interneurons are involved in modulating barrel cortex activity and perception during active whisking. Here we identify a developmental transition point of structural and functional rearrangements onto these interneurons around the start of active sensation at P14. Using in vivo two-photon Ca2+ imaging, we find that before P14, both interneuron types respond stronger to a multi-whisker stimulus, whereas after P14 their responses diverge, with VIP+ cells losing their multi-whisker preference and SST+ neurons enhancing theirs. Additionally, we find that Ca2+ signaling dynamics increase in precision as the cells and network mature. Rabies virus tracings followed by tissue clearing, as well as photostimulation-coupled electrophysiology reveal that SST+ cells receive higher cross-barrel inputs compared to VIP+ neurons at both time points. In addition, whereas prior to P14 both cell types receive direct input from the sensory thalamus, after P14 VIP+ cells show reduced inputs and SST+ cells largely shift to motor-related thalamic nuclei.

Constrained brain volume in an efficient coding model explains the fraction of excitatory and inhibitory neurons in sensory cortices

The number of neurons in mammalian cortex varies by multiple orders of magnitude across different species. In contrast, the ratio of excitatory to inhibitory neurons (E:I ratio) varies in a much smaller range, from 3:1 to 9:1 and remains roughly constant for different sensory areas within a species. Despite this structure being important for understanding the function of neural circuits, the reason for this consistency is not yet understood. While recent models of vision based on the efficient coding hypothesis show that increasing the number of both excitatory and inhibitory cells improves stimulus representation, the two cannot increase simultaneously due to constraints on brain volume. In this work, we implement an efficient coding model of vision under a volume (i.e., total number of neurons) constraint while varying the E:I ratio. We show that the performance of the model is optimal at biologically observed E:I ratios under several metrics. We argue that this happens due to trade-offs between the computational accuracy and the representation capacity for natural stimuli. Further, we make experimentally testable predictions that 1) the optimal E:I ratio should be higher for species with a higher sparsity in the neural activity and 2) the character of inhibitory synaptic distributions and firing rates should change depending on E:I ratio. Our findings, which are supported by our new preliminary analyses of publicly available data, provide the first quantitative and testable hypothesis based on optimal coding models for the distribution of neural types in the mammalian sensory cortices.

Tracking stimulus representation across a 2-back visual working memory task

How does the neural representation of visual working memory content vary with behavioural priority? To address this, we recorded electroencephalography (EEG) while subjects performed a continuous-performance 2-back working memory task with oriented-grating stimuli. We tracked the transition of the neural representation of an item ( n ) from its initial encoding, to the status of ‘unprioritized memory item' (UMI), and back to ‘prioritized memory item', with multivariate inverted encoding modelling. Results showed that the representational format was remapped from its initially encoded format into a distinctive ‘opposite' representational format when it became a UMI and then mapped back into its initial format when subsequently prioritized in anticipation of its comparison with item n + 2. Thus, contrary to the default assumption that the activity representing an item in working memory might simply get weaker when it is deprioritized, it may be that a process of priority-based remapping helps to protect remembered information when it is not in the focus of attention.

Devaluation-sensitive responding to preconditioned cues requires orbitofrontal cortex during initial cue-cue learning

The orbitofrontal cortex (OFC) is necessary for value inference in tests of model-based reasoning. This ability could be accounted for by either representation of value or by representation of broader associative structure. Our lab recently reported correlates of both value and of valueless associative structure in OFC using single-unit recording (Sadacca et al., 2018). This incidental stimulus-stimulus representation was surprising since OFC was thought to be involved only when items of biological significance were driving responses. However, we did not assess whether this activity was necessary for encoding the associative information that would contribute to value inference during probe testing. Here, we used optogenetic OFC inhibition during sensory preconditioning to test this. We found that OFC inhibition during preconditioning impaired value inference during the probe test, demonstrating that the correlates we previously observed are not simply downstream readouts of sensory processing and instead contribute to encoding valueless sensory associative information.

Developmental Divergence of Sensory Stimulus Representation in Cortical Interneurons

Two inhibitory cell types involved in modulating barrel cortex activity and perception during active whisking in adult mice, are the VIP+ and SST+ interneurons. Here we identify a developmental transition point of structural and functional rearrangements onto these interneuron types around the start of active sensation at P14. Using in vivo two-photon Ca2+ imaging, we find that before P14, both interneuron types respond stronger to a multi-whisker stimulus, whereas after P14 their responses diverge, with VIP+ cells losing their multi-whisker preference and SST+ neurons enhancing theirs. Rabies virus tracings followed by tissue clearing, as well as photostimulation-coupled electrophysiology reveal that SST+ cells receive higher cross-barrel inputs compared to VIP+ at both time points. In addition, we also uncover that whereas prior to P14 both cell types receive direct input from the sensory thalamus, after P14 VIP+ cells show reduced inputs and SST+ cells largely shift to motor-related thalamic nuclei.

Prefrontal cortex represents heuristics that shape choice bias and its integration into future behavior

SummaryGoal-directed behavior requires integrating sensory information with prior knowledge about the environment. Behavioral biases that arise from these priors could increase positive outcomes when the priors match the true structure of the environment, but mismatches also happen frequently and could cause unfavorable outcomes. Biases that reduce gains and fail to vanish with training indicate fundamental suboptimalities arising from ingrained heuristics of the brain. Here, we report systematic, gain-reducing choice biases in highly-trained monkeys performing a motion direction discrimination task where only the current stimulus is behaviorally relevant. The monkey’s bias fluctuated at two distinct time scales: slow, spanning tens to hundreds of trials, and fast, arising from choices and outcomes of the most recent trials. Our finding enabled single trial prediction of biases, which influenced the choice especially on trials with weak stimuli. The pre-stimulus activity of neuronal ensembles in the monkey prearcuate gyrus represented these biases as an offset along the decision axis in the state space. This offset persisted throughout the stimulus viewing period, when sensory information was integrated, leading to a biased choice. The pre-stimulus representation of history-dependent bias was functionally indistinguishable from the neural representation of upcoming choice before stimulus onset, validating our model of single-trial biases and suggesting that pre-stimulus representation of choice could be fully defined by biases inferred from behavioral history. Our results indicate that the prearcuate gyrus reflects intrinsic heuristics that compute bias signals, as well as the mechanisms that integrate them into the oculomotor decision-making process.