Spatial inference without a cognitive map: the role of higher-order path integration

Experience-Dependent Egr1 Expression in the Hippocampus of Japanese Quail

The hippocampal formation (HF) is a structure critical to navigation and many forms of memory. In mammals, the firing of place cells is widely regarded as the fundamental unit of HF information processing. Supporting homology between the avian and mammalian HF, context-specific patterns of Egr1 have been reported in birds that are comparable to those produced by place cell firing in mammals. Recent electrophysiological data, however, suggest that many avian species lack place cells, potentially undermining the correspondence between Egr1 and place cell-related firing in the avian brain. To clarify this, the current study examines Egr1 expression in Japanese quail under conditions known to elicit only weakly spatially modulated firing patterns and report robust context-dependent Egr1 expression. These data confirm that context-dependent expression of Egr1 is not dependent on precise place fields and provide insight into how these birds are able to perform complex spatial tasks despite lacking mammalian-like place cells.

Spatialization of Time in the Entorhinal-Hippocampal System

The functional role of the entorhinal-hippocampal system has been a long withstanding mystery. One key theory that has become most popular is that the entorhinal-hippocampal system represents space to facilitate navigation in one's surroundings. In this Perspective article, I introduce a novel idea that undermines the inherent uniqueness of spatial information in favor of time driving entorhinal-hippocampal activity. Specifically, by spatializing events that occur in succession (i.e., across time), the entorhinal-hippocampal system is critical for all types of cognitive representations. I back up this argument with empirical evidence that hints at a role for the entorhinal-hippocampal system in non-spatial representation, and computational models of the logarithmic compression of time in the brain.

Higher-Order Conditioning in the Spatial Domain

Spatial learning and memory, the processes through which a wide range of living organisms encode, compute, and retrieve information from their environment to perform goal-directed navigation, has been systematically investigated since the early twentieth century to unravel behavioral and neural mechanisms of learning and memory. Early theories about learning to navigate space considered that animals learn through trial and error and develop responses to stimuli that guide them to a goal place. According to a trial-and error learning view, organisms can learn a sequence of motor actions that lead to a goal place, a strategy referred to as response learning, which contrasts with place learning where animals learn locations with respect to an allocentric framework. Place learning has been proposed to produce a mental representation of the environment and the cartesian relations between stimuli within it-which Tolman coined the cognitive map. We propose to revisit some of the best empirical evidence of spatial inference in animals, and then discuss recent attempts to account for spatial inferences within an associative framework as opposed to the traditional cognitive map framework. We will first show how higher-order conditioning can successfully account for inferential goal-directed navigation in a variety of situations and then how vectors derived from path integration can be integrated via higher-order conditioning, resulting in the generation of higher-order vectors that explain novel route taking. Finally, implications to cognitive map theories will be discussed.

Higher-Order Conditioning and Dopamine: Charting a Path Forward

Higher-order conditioning involves learning causal links between multiple events, which then allows one to make novel inferences. For example, observing a correlation between two events (e.g., a neighbor wearing a particular sports jersey), later helps one make new predictions based on this knowledge (e.g., the neighbor's wife's favorite sports team). This type of learning is important because it allows one to benefit maximally from previous experiences and perform adaptively in complex environments where many things are ambiguous or uncertain. Two procedures in the lab are often used to probe this kind of learning, second-order conditioning (SOC) and sensory preconditioning (SPC). In second-order conditioning (SOC), we first teach subjects that there is a relationship between a stimulus and an outcome (e.g., a tone that predicts food). Then, an additional stimulus is taught to precede the predictive stimulus (e.g., a light leads to the food-predictive tone). In sensory preconditioning (SPC), this order of training is reversed. Specifically, the two neutral stimuli (i.e., light and tone) are first paired together and then the tone is paired separately with food. Interestingly, in both SPC and SOC, humans, rodents, and even insects, and other invertebrates will later predict that both the light and tone are likely to lead to food, even though they only experienced the tone directly paired with food. While these processes are procedurally similar, a wealth of research suggests they are associatively and neurobiologically distinct. However, midbrain dopamine, a neurotransmitter long thought to facilitate basic Pavlovian conditioning in a relatively simplistic manner, appears critical for both SOC and SPC. These findings suggest dopamine may contribute to learning in ways that transcend differences in associative and neurological structure. We discuss how research demonstrating that dopamine is critical to both SOC and SPC places it at the center of more complex forms of cognition (e.g., spatial navigation and causal reasoning). Further, we suggest that these more sophisticated learning procedures, coupled with recent advances in recording and manipulating dopamine neurons, represent a new path forward in understanding dopamine's contribution to learning and cognition.