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We develop a mathematical approach to formally proving that certain neural computations and representations exist based on patterns observed in an organism's behaviour. To illustrate, we provide a simple set of conditions under which an ant's ability to determine how far it is from its nest would logically imply neural structures isomorphic to the natural numbers ℕ. We generalise these results to arbitrary behaviours and representations and show what mathematical characterisation of neural computation and representation is simplest while being maximally predictive of behaviour. We develop this framework in detail using a path integration example, where an organism's ability to search for its nest in the correct location implies representational structures isomorphic to two‐dimensional coordinates under addition. We also study a system for processing anbn strings common in comparative work. Our approach provides an objective way to determine what theory of a physical system is best, addressing a fundamental challenge in neuroscientific inference. These results motivate considering which neurobiological structures have the requisite formal structure and are otherwise physically plausible given relevant physical considerations such as generalisability, information density, thermodynamic stability and energetic cost. [ABSTRACT FROM AUTHOR]

Reinforcement learning inspires much theorizing in neuroscience, cognitive science, machine learning, and AI. A central question concerns the conditions that produce the perception of a contingency between an action and reinforcement--the assignment-of-credit problem. Contemporary models of associative and reinforcement learning do not leverage the temporal metrics (measured intervals). Our information-theoretic approach formalizes contingency by time-scale invariant temporal mutual information. It predicts that learning may proceed rapidly even with extremely long action--reinforcer delays. We show that rats can learn an action after a single reinforcement, even with a 16-min delay between the action and reinforcement (15-fold longer than any delay previously shown to support such learning). By leveraging metric temporal information, our solution obviates the need for windows of associability, exponentially decaying eligibility traces, microstimuli, or distributions over Bayesian belief states. Its three equations have no free parameters; they predict one-shot learning without iterative simulation. [ABSTRACT FROM AUTHOR]

The effects of altering the contingency between the conditioned stimulus (CS) and the unconditioned stimulus (US) on the acquisition of autoshaped responding was investigated by changing the frequency of unsignaled USs during the intertrial interval. The addition of the unsignaled USs had an effect on acquisition speed comparable with that of massing trials. The effects of these manipulations can be understood in terms of their effect on the amount of information (number of bits) that the average CS conveys to the subject about the timing of the next US. The number of reinforced CSs prior to acquisition is inversely related to the information content of the CS. Keywords: Pavlovian conditioning, contingency, uncertainty, time, information

Information theory provides a quantitative conceptual framework for understanding the flow of information from the world into and through brains. It focuses our attention on the sets of possible messages a brain's anatomy and physiology enable it to receive. The meanings of the messages arise from the inferences licensed by the brain's processing of them. Different meanings arise at different levels because different representations of the input license different inferences. [ABSTRACT FROM AUTHOR]

Numerosity, or the ability to understand and distinguish between discrete quantities, was first formalized for study in animals by Mechner (1958a). Rats had to press one lever (the counting lever) n times to arm food release from pressing a second lever (the reward lever). The only cue that n presses had been made to the counting lever was the animal's representation of how many times it had pressed it. In the years that have passed since, many researchers have modified the task in meaningful ways to attempt to tease apart timing-based and count-based strategies. Strong evidence has amassed that the two are fundamentally different and separable skills but, to date, no study has effectively examined the differential contributions of the two strategies in Mechner's original task. By examining performance mid-trial and correlating it with whole-trial performance, we were able to identify patterns of correlation consistent with counting and timing strategies. Due to the independent nature of these correlation patterns, this technique was uniquely able to provide evidence for strategies that combined both timing and counting components. The results show that most mice demonstrated this combined strategy. This provides direct evidence that mice can and do use numerosity to complete Mechner's original task. A rational agent with fallible estimates of both counts made and time elapsed in making them should use both estimates when deciding when to switch to the second lever. [ABSTRACT FROM AUTHOR]

Human and mouse subjects tried to anticipate at which of 2 locations a reward would appear. On a randomly scheduled fraction of the trials, it appeared with a short latency at one location; on the complementary fraction, it appeared after a longer latency at the other location. Subjects of both species accurately assessed the exogenous uncertainty (the probability of a short versus a long trial) and the endogenous uncertainty (from the scalar variability in their estimates of an elapsed duration) to compute the optimal target latency for a switch from the short- to the long-latency location. The optimal latency was arrived at so rapidly that there was no reliably discernible improvement over trials. Under these nonverbal conditions, humans and mice accurately assess risks and behave nearly optimally. That this capacity is well-developed in the mouse opens up the possibility of a genetic approach to the neurobiological mechanisms underlying risk assessment. [ABSTRACT FROM AUTHOR]

Contemporary theories guiding the search for neural mechanisms of learning and memory assume that associative learning results from the temporal pairing of cues and reinforcers resulting in coincident activation of associated neurons, strengthening their synaptic connection. While enduring, this framework has limitations: Temporal pairing-based models of learning do not fit with many experimental observations and cannot be used to make quantitative predictions about behavior. Here, we present behavioral data that support an alternative, information-theoretic conception: The amount of information that cues provide about the timing of reward delivery predicts behavior. Furthermore, this approach accounts for the rate and depth of both inhibitory and excitatory learning across paradigms and species. We also show that dopamine release in the ventral striatum reflects cue-predicted changes in reinforcement rates consistent with subjects understanding temporal relationships between task events. Our results reshape the conceptual and biological framework for understanding associative learning. [ABSTRACT FROM AUTHOR]

In Pavlovian conditioning, the strength of a conditioned response is a function of the probability of reinforcement. However, manipulations of probability are often confounded with changes in the rate of reinforcement. Two between-group experiments in mice evaluated the effect of the probability of reinforcement, while controlling the rate of reinforcement, on appetitive conditioning and extinction. Experiment 1 equated the reinforcement rate by manipulating the number of reinforcements received in each reinforced trial in a critical group (one vs. two consecutive rewards). The results of this experiment showed that probability influenced the rate of responses in acquisition, even when controlling the reinforcement rate. Experiment 2 further assessed the role of probability on behavior while controlling the rate of reinforcement during the conditioned stimulus (CS) using a split-trial design, in which the total CS time was held constant but presented in different numbers of discrete trials (e.g., 50% reinforcement with two 12 s CS's vs. 100% reinforcement with a 24 s average CS duration). This experiment confirmed that probability influenced response rates, and both the probability and rate of reinforcement affected the proportion of trials with responses. Together, these results suggest that the probability of reinforcement, while having little effect on the speed at which responses emerged, affects responding even when the rate of reinforcement is held constant. The results challenge formal learning theories to account for the effects of both the probability and rate of reinforcement. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Honeybees ( Apis mellifera carnica ) communicate the direction and distance to a food source by means of a waggle dance. We ask whether bees recruited by the dance use it only as a flying instruction, with the technical form of a polar vector, or also translate it into a location vector that enables them to set courses directed toward the food source from arbitrary locations within their familiar territory. The flights of recruits captured on exiting the hive and released at distant sites were tracked by radar. The recruits performed first a straight flight in approximately the compass direction indicated by the dance. However, this "vector" portion of their flights and the ensuing tortuous "search" portion were strongly and differentially affected by the release site. Searches were biased toward the true location of the food and away from the location specified by translating the origin for the danced polar vector to the release site. We conclude that by following the dance recruits get two messages, a polar flying instruction (bearing and range from the hive) and a location vector that enables them to approach the source from anywhere in their familiar territory. The dance communication is much richer than thought so far.

Temporal information-processing is critical for adaptive behavior and goal-directed action. It is thus crucial to understand how the temporal distance between behaviorally relevant events is encoded to guide behavior. However, research on temporal representations has yielded mixed findings as to whether organisms utilize relative versus absolute judgments of time intervals. To address this fundamental question about the timing mechanism, we tested mice in a duration discrimination procedure in which they learned to correctly categorize tones of different durations as short or long. After being trained on a pair of target intervals, the mice were transferred to conditions in which cue durations and corresponding response locations were systematically manipulated so that either the relative or absolute mapping remained constant. The findings indicate that transfer occurred most readily when relative relationships of durations and response locations were preserved. In contrast, when subjects had to re-map these relative relations, even when positive transfer initially occurred based on absolute mappings, their temporal discrimination performance was impaired, and they required extensive training to re-establish temporal control. These results demonstrate that mice can represent experienced durations both as having a certain magnitude (absolute representation) and as being shorter or longer of the two durations (an ordinal relation to other cue durations), with relational control having a more enduring influence in temporal discriminations. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Numbers are symbols manipulated in accord with the axioms of arithmetic. They sometimes represent discrete and continuous quantities (e.g., numerosities, durations, rates, distances, directions, and probabilities), but they are often simply names. Brains, including insect brains, represent the rational numbers with a fixed-point data type, consisting of a significand and an exponent, thereby conveying both magnitude and precision.

Shannon's theory lays the foundation for understanding the flow of information from world into brain: There must be a set of possible messages. Brain structure determines what they are. Many messages convey quantitative facts (distances, directions, durations, etc.). It is impossible to consider how neural tissue processes these numbers without first considering how it encodes them.

Animals optimize their behavior to maximize rewards by utilizing cues from the environment. In discrimination learning, cues signal when rewards can and cannot be earned by making a particular response. In our experiment, we trained male mice to press a lever to receive a reward on a random interval schedule. We then introduced a prolonged tone (20, 40, or 80 sec), during which no rewards could be earned. We sought to test our hypothesis that the duration of the tone and frequency of reward during the inter-tone-intervals affect the informativeness of cues and led to differences in discriminative behavior. Learning was expressed as an increase in lever pressing during the intertrial interval (ITI) and, when the informativeness of the cue was high, animals also reduced their lever pressing during the tone. Additionally, we found that the depth of discriminative learning was linearly related to the informativeness of the cues. Our results show that the time-scale invariant information-theoretic definition of contingency applied to excitatory conditioning can also be applied to inhibitory conditioning. (PsycINFO Database Record (c) 2019 APA, all rights reserved).