Randomness impacts the building of specific priors, visual exploration, and perception in object recognition.

Recognising objects is a vital skill on which humans heavily rely to respond quickly and adaptively to their environment. Yet, we lack a full understanding of the role visual information sampling plays in this process, and its relation to the individual's priors. To bridge this gap, the eye-movements of 18 adult participants were recorded during a free-viewing object-recognition task using Dots stimuli1. Participants viewed the stimuli in one of three orders: from most visible to least (Descending), least visible to most (Ascending), or in a randomised order (Random). This dictated the strength of their priors along the experiment. Visibility order influenced the participants' recognition performance and visual exploration. In addition, we found that while orders allowing for stronger priors generally led participants to visually sample more informative locations, this was not the case of Random participants. Indeed, they appeared to behave naïvely, and their use of specific object-related priors was fully impaired, while they maintained the ability to use general, task-related priors to guide their exploration. These findings have important implications for our understanding of perception, which appears to be influenced by complex cognitive processes, even at the basic level of visual sampling during object recognition.

Fast updating feedback from piriform cortex to the olfactory bulb relays multimodal reward contingency signals during rule-reversal.

While animals readily adjust their behavior to adapt to relevant changes in the environment, the neural pathways enabling these changes remain largely unknown. Here, using multiphoton imaging, we investigated whether feedback from the piriform cortex to the olfactory bulb supports such behavioral flexibility. To this end, we engaged head-fixed mice in a multimodal rule-reversal task guided by olfactory and auditory cues. Both odor and, surprisingly, the sound cues triggered cortical bulbar feedback responses which preceded the behavioral report. Responses to the same sensory cue were strongly modulated upon changes in stimulus-reward contingency (rule reversals). The re-shaping of individual bouton responses occurred within seconds of the rule-reversal events and was correlated with changes in the behavior. Optogenetic perturbation of cortical feedback within the bulb disrupted the behavioral performance. Our results indicate that the piriform-to-olfactory bulb feedback carries reward contingency signals and is rapidly re-formatted according to changes in the behavioral context.

The fractal brain: scale-invariance in structure and dynamics.

The past 40 years have witnessed extensive research on fractal structure and scale-free dynamics in the brain. Although considerable progress has been made, a comprehensive picture has yet to emerge, and needs further linking to a mechanistic account of brain function. Here, we review these concepts, connecting observations across different levels of organization, from both a structural and functional perspective. We argue that, paradoxically, the level of cortical circuits is the least understood from a structural point of view and perhaps the best studied from a dynamical one. We further link observations about scale-freeness and fractality with evidence that the environment provides constraints that may explain the usefulness of fractal structure and scale-free dynamics in the brain. Moreover, we discuss evidence that behavior exhibits scale-free properties, likely emerging from similarly organized brain dynamics, enabling an organism to thrive in an environment that shares the same organizational principles. Finally, we review the sparse evidence for and try to speculate on the functional consequences of fractality and scale-freeness for brain computation. These properties may endow the brain with computational capabilities that transcend current models of neural computation and could hold the key to unraveling how the brain constructs percepts and generates behavior.

Sources of bias in single-trial normalization procedures.

Baseline normalization procedures are essential for the analysis of brain activity. These use statistics of a reference (baseline) period to normalize data along the entire trial (baseline and stimulus periods). A very popular procedure is pseudo z-scoring, traditionally applied to time-frequency spectral power estimates, where it was recently shown to generate positive bias. Bias was thought to arise because of outliers stemming from the skewed distribution of spectral power values. Here we challenge this view and causally show that bias originates from a more general problem that affects a wide array of normalization techniques, including some that are routinely used. We show that bias is caused by the division of correlated terms and that it depends directly on the sign and magnitude of correlation between the numerator and denominator. Correlation emerges either from the properties of the data being normalized or from the properties of the normalization method. z-scoring produces bias when source data have a skewed distribution but it is bias-free when the distribution is symmetric, while methods such as dF/F for fluorescence data lead to bias because the numerator and denominator are inherently correlated. We provide a simple, fast and general solution to reduce and even eliminate bias by welding (fusing) baseline periods of multiple trials into a single, large baseline. This method is generic, can be used to normalize individual trials and provides bias-free estimates given a long enough extended baseline. We show that baseline fusing is superior to more complex techniques that have been proposed before.