Long-lasting forms of plasticity through patterned ultrasound-induced brainwave entrainment.

Achieving long-lasting neuronal modulation with low-intensity, low-frequency ultrasound is challenging. Here, we devised theta burst ultrasound stimulation (TBUS) with gamma bursts for brain entrainment and modulation of neuronal plasticity in the mouse motor cortex. We demonstrate that two types of TBUS, intermittent and continuous TBUS, induce bidirectional long-term potentiation or depression-like plasticity, respectively, as evidenced by changes in motor-evoked potentials. These effects depended on molecular pathways associated with long-term plasticity, including N-methyl-d-aspartate receptor and brain-derived neurotrophic factor/tropomyosin receptor kinase B activation, as well as de novo protein synthesis. Notably, bestrophin-1 and transient receptor potential ankyrin 1 play important roles in these enduring effects. Moreover, pretraining TBUS enhances the acquisition of previously unidentified motor skills. Our study unveils a promising protocol for ultrasound neuromodulation, enabling noninvasive and sustained modulation of brain function.

Automating licking bias correction in a two-choice delayed match-to-sample task to accelerate learning.

Animals often display choice bias, or a preference for one option over the others, which can significantly impede learning new tasks. Delayed match-to-sample (DMS) tasks with two-alternative choices of lickports on the left and right have been widely used to study sensory processing, working memory, and associative memory in head-fixed animals. However, extensive training time, primarily due to the animals' biased licking responses, limits their practical utility. Here, we present the implementation of an automated side bias correction system in an olfactory DMS task, where the lickport positions and the ratio of left- and right-rewarded trials are dynamically adjusted to counterbalance mouse's biased licking responses during training. The correction algorithm moves the preferred lickport farther away from the mouse's mouth and the non-preferred lickport closer, while also increasing the proportion of non-preferred side trials when biased licking occurs. We found that adjusting lickport distances and the proportions of left- versus right-rewarded trials effectively reduces the mouse's side bias. Further analyses reveal that these adjustments also correlate with subsequent improvements in behavioral performance. Our findings suggest that the automated side bias correction system is a valuable tool for enhancing the applicability of behavioral tasks involving two-alternative lickport choices.

Dynamic and stable hippocampal representations of social identity and reward expectation support associative social memory in male mice.

Recognizing an individual and retrieving and updating the value information assigned to the individual are fundamental abilities for establishing social relationships. To understand the neural mechanisms underlying the association between social identity and reward value, we developed Go-NoGo social discrimination paradigms that required male subject mice to distinguish between familiar mice based on their individually unique characteristics and associate them with reward availability. We found that mice could discriminate individual conspecifics through a brief nose-to-nose investigation, and this ability depended on the dorsal hippocampus. Two-photon calcium imaging revealed that dorsal CA1 hippocampal neurons represented reward expectation during social, but not non-social tasks, and these activities were maintained over days regardless of the identity of the associated mouse. Furthermore, a dynamically changing subset of hippocampal CA1 neurons discriminated between individual mice with high accuracy. Our findings suggest that the neuronal activities in CA1 provide possible neural substrates for associative social memory.

The Representational Dynamics of Sequential Perceptual Averaging.

It is clear that humans can extract statistical information from streams of visual input, yet how our brain processes sequential images into the abstract representation of the mean feature value remains poorly explored. Using multivariate pattern analyses of electroencephalography recorded while human observers viewed 10 sequentially presented Gabors of different orientations to estimate their mean orientation at the end, we investigated sequential averaging mechanism by tracking the quality of individual and mean orientation as a function of sequential position. Critically, we varied the sequential variance of Gabor orientations to understand the neural basis of perceptual mean errors occurring during a sequential averaging task. We found that the mean-orientation representation emerged at specific delays from each sequential stimulus onset and became increasingly accurate as additional Gabors were viewed. Especially in frontocentral electrodes, the neural representation of mean orientation improved more rapidly and to a greater degree in less volatile environments, whereas individual orientation information was encoded precisely regardless of environmental volatility. The computational analysis of behavioral data also showed that perceptual mean errors arise from the cumulative construction of the mean orientation rather than the low-level encoding of individual stimulus orientation. Thus, our findings provide neural mechanisms to differentially accumulate increasingly abstract features from a concrete piece of information across the cortical hierarchy depending on environmental volatility.SIGNIFICANCE STATEMENT The visual system extracts behaviorally relevant summary statistical representation by exploiting statistical regularity of the visual stream over time. However, how the neural representation of the abstract mean feature value develops in a temporally changing environment remains poorly identified. Here, we directly recover the mean orientation information of sequentially delivered Gabor stimuli with different orientations as a function of their positions in time. The mean orientation representation, which is regularly updated, becomes increasingly accurate with increasing sequential position especially in the frontocentral region. Further, perceptual mean errors arise from the cumulative process rather than the low-level stimulus encoding. Overall, our study reveals a role of higher cortical areas in integrating stimulus-specific information into increasingly abstract task-oriented information.