Mattias Horan

We argue that the type of meta-learning proposed by Binz et al. generates models with low interpretability and falsifiability that have limited usefulness for neuroscience research. An alternative approach to meta-learning based on hyperparameter optimization obviates these concerns and can generate empirically testable hypotheses of biological computations.

Neuropixels probes represent the state-of-the-art for high-yield electrophysiology in neuroscience: the simultaneous recording of hundreds of neurons is now routinely carried out in head-restrained animals. In contrast, neural recording in unrestrained animals, as well as recording and tracking neurons over days, remains challenging, though it is possible using chronic implants. A major challenge is the availability of simple methods that can be implemented with limited or no prior experience with Neuropixels probes, while achieving reliable, reusable, versatile high-density electrophysiology. Here we developed, deployed, and evaluated the real-world performance of Repix, a chronic implantation system that permits the repeated re-use of Neuropixels probes. The lightweight system allows implanted animals to express a full range of natural behaviors, including social behaviors. We show that Repix allows the recording of hundreds of neurons across many months, up to a year, with implants across cortical and subcortical brain regions. Probes can be reused repeatedly with stable yield. Repix has been used by 16 researchers in 10 laboratories to date, and we evaluated the real-world performance of Repix in a variety of chronic recording paradigms in both mice and rats with a combined 209 implantations. We found that the key advantage of Repix is robustness and simplicity. Adopters of Repix became proficient at five procedures on average, regardless of prior experience with in vivo electrophysiology. With the companion protocol alongside this article, the performance and user-friendliness of Repix should facilitate a wide uptake of chronic Neuropixels recordings.

Neuropixels probes represent the state-of-the-art for high-yield electrophysiology in neuroscience: the simultaneous recording of hundreds of neurons is now routinely carried out in head-restrained animals. In contrast, neural recording in unrestrained animals, as well as recording and tracking neurons over days, remains challenging, though it is possible using chronic implants. A major challenge is the availability of simple methods that can be implemented with limited or no prior experience with Neuropixels probes, while achieving reliable, reusable, versatile high-density electrophysiology. Here we developed, deployed, and evaluated the real-world performance of Repix, a chronic implantation system that permits the repeated re-use of Neuropixels probes. The lightweight system allows implanted animals to express a full range of natural behaviors, including social behaviors. We show that Repix allows the recording of hundreds of neurons across many months, up to a year, with implants across cortical and subcortical brain regions. Probes can be reused repeatedly with stable yield. Repix has been used by 16 researchers in 10 laboratories to date, and we evaluated the real-world performance of Repix in a variety of chronic recording paradigms in both mice and rats with a combined 209 implantations. We found that the key advantage of Repix is robustness and simplicity. Adopters of Repix became proficient at five procedures on average, regardless of prior experience with in vivo electrophysiology. With the companion protocol alongside this article, the performance and user-friendliness of Repix should facilitate a wide uptake of chronic Neuropixels recordings.

This is the protocol associated with Repix: reliable, reusable, versatile chronic Neuropixels implants using minimal components. In the main report, we describe the development, deployment, and evaluation of Repix, a chronic implantation system that permits the repeated re-use of the Neuropixels probes and characterized this system for a variety of use cases. This protocol is appropriate for use in -Both unrestrained and restrained animals performing a wide variety of behaviors as decision-making, social behaviors, foraging, and sleep -Mice and rats -Neuropixels 1.0 or 2.0 (as well as Neuronexus probes) This protocol describes the assembly, implantation and explantation of probes using Repix.

Animals are intrinsically motivated to resolve uncertainty and predict future events. This motivation is encoded in cortical and subcortical structures, but a key open question is how it generates concrete policies for attending to informative stimuli. We examined this question using neural recordings in the monkey lateral intraparietal area (LIP), a visual area implicated in attention and gaze, during non-instrumental information demand. We show that the uncertainty that was resolved by a visual cue enhanced visuo-spatial responses of LIP cells independently of reward probability. This enhancement was independent of immediate saccade plans but correlated with the sensitivity to uncertainty in eye movement behavior on longer time scales (across sessions/days). The findings suggest that topographic visual maps receive motivational signals of uncertainty, which enhance the priority of informative stimuli and the likelihood that animals will orient to the stimuli to reduce uncertainty.

Gathering information is crucial for maximizing fitness, but requires diverting resources from searching directly for primary rewards to actively exploring the environment. Optimal decision-making thus maximizes information while reducing effort costs, but little is known about the neural implementation of these tradeoffs. We present a Reinforcement Meta-Learning (RML) computational mechanism that solves the trade-offs between the value and costs of gathering information. We implement the RML in a biologically plausible architecture that links catecholaminergic neuromodulators, the medial prefrontal cortex and topographically organized visual maps and show that it accounts for neural and behavioral findings on information demand motivated by instrumental incentives and intrinsic utility. Moreover, the utility function used by the RML, encoded by dopamine, is an approximation of free-energy. Thus, the RML presents a biologically plausible mechanism through which coordinated motivational, executive and sensory systems generate visual information gathering policies that minimize free energy.

During natural behavior, animals actively gather information that is relevant for learning or actions; however, the mechanisms of active sampling are rarely investigated. We tested parietal neurons involved in oculomotor control in a task in which monkeys made saccades to gather visual information relevant to a subsequent action. We show that the neurons encode, before the saccade, the information gain (reduction in decision uncertainty) that the saccade was expected to bring for the following action. Sensitivity to information gain correlates with the monkeys’ efficiency at processing the information in the post-saccadic fixation, but is independent of neuronal reward sensitivity. Reward sensitivity, in turn, is unreliable across task contexts, inconsistent with the view that the cells encode economic utility. The findings suggest that parietal cells involved in oculomotor decisions show uncertainty-dependent boosts of neural gain that facilitate the implementation of active sampling policies, including the selection of relevant cues and the efficient use of the information delivered by these cues.

The lac promoter is one of the most commonly used promoters for expression control of recombinant genes in E. coli. In the absence of galactosides, the lac promoter is repressed by its repressor protein LacI. Since the lac promoter is regulated by a repressor, overexpression of LacI is necessary for regulation when the promoter is introduced on a high-copy plasmid. For that purpose, a modified variant of LacI, a LVA-tagged LacI, was submitted to the Registry of Standard Biological Parts and has been used for more than 500 constructs since then. We have found, however, that natural LacI is superior to the LVA-tagged LacI as controller of expression.