Local and Global Contrast Adaptation in Retinal Ganglion Cells

SummaryRetinal ganglion cells react to changes in visual contrast by adjusting their sensitivity and temporal filtering characteristics. This contrast adaptation has primarily been studied under spatially homogeneous stimulation. Yet, ganglion cell receptive fields are often characterized by spatial subfields, providing a substrate for nonlinear spatial processing. This raises the question whether contrast adaptation follows a similar subfield structure or whether it occurs globally over the receptive field even for local stimulation. We therefore recorded ganglion cell activity in isolated salamander retinas while locally changing visual contrast. Ganglion cells showed primarily global adaptation characteristics, with notable exceptions in certain aspects of temporal filtering. Surprisingly, some changes in filtering were most pronounced for locations where contrast did not change. This seemingly paradoxical effect can be explained by a simple computational model, which emphasizes the importance of local nonlinearities in the retina and suggests a reevaluation of previously reported local contrast adaptation

Data from: A map of abstract relational knowledge in the human hippocampal–entorhinal cortex

The hippocampal–entorhinal system encodes a map of space that guides spatial navigation. Goal-directed behaviour outside of spatial navigation similarly requires a representation of abstract forms of relational knowledge. This information relies on the same neural system, but it is not known whether the organisational principles governing continuous maps may extend to the implicit encoding of discrete, non-spatial graphs. Here, we show that the human hippocampal–entorhinal system can represent relationships between objects using a metric that depends on associative strength. We reconstruct a map-like knowledge structure directly from a hippocampal–entorhinal functional magnetic resonance imaging adaptation signal in a situation where relationships are non-spatial rather than spatial, discrete rather than continuous, and unavailable to conscious awareness. Notably, the measure that best predicted a behavioural signature of implicit knowledge and blood oxygen level-dependent adaptation was a weighted sum of future states, akin to the successor representation that has been proposed to account for place and grid-cell firing patterns

Contagion of temporal discounting value preferences in neurotypical and autistic adults

Neuroeconomics paradigms have demonstrated that learning about another’s beliefs can make you more like them (i.e., contagion). Due to social deficits in autism, it is possible that autistic individuals will be immune to contagion. We fit Bayesian computational models to a temporal discounting task, where participants made decisions for themselves before and after learning the distinct preferences of two others. Two independent neurotypical samples (N = 48; N = 98) both showed a significant contagion effect; however the strength of contagion was unrelated to autistic traits. Equivalence tests showed autistic (N = 12) and matched neurotypical N = 12) samples had similar levels of contagion and accuracy when learning about others. Despite social impairments being at the core of autistic symptomatology, contagion of value preferences appears to be intact. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10803-021-04962-5

Task state representations in vmPFC mediate relevant and irrelevant value signals and their behavioral influence

Abstract The ventromedial prefrontal-cortex (vmPFC) is known to contain expected value signals that inform our choices. But expected values even for the same stimulus can differ by task. In this study, we asked how the brain flexibly switches between such value representations in a task-dependent manner. Thirty-five participants alternated between tasks in which either stimulus color or motion predicted rewards. We show that multivariate vmPFC signals contain a rich representation that includes the current task state or context (motion/color), the associated expected value, and crucially, the irrelevant value of the alternative context. We also find that irrelevant value representations in vmPFC compete with relevant value signals, interact with task-state representations and relate to behavioral signs of value competition. Our results shed light on vmPFC’s role in decision making, bridging between its role in mapping observations onto the task states of a mental map, and computing expected values for multiple states

Correction: Similarities and differences in spatial and non-spatial cognitive maps.

[This corrects the article DOI: 10.1371/journal.pcbi.1008149.]

Subcortical amygdala pathways enable rapid face processing

Human faces may signal relevant information and are therefore analysed rapidly and effectively by the brain. However, the precise mechanisms and pathways involved in rapid face processing are unclear. One view posits a role for a subcortical connection between early visual sensory regions and the amygdala, while an alternative account emphasises cortical mediation. To adjudicate between these functional architectures, we recorded magnetoencephalographic (MEG) evoked fields in human subjects to presentation of faces with varying emotional valence. Early brain activity was better explained by dynamic causal models containing a direct subcortical connection to the amygdala irrespective of emotional modulation. At longer latencies, models without a subcortical connection had comparable evidence. Hence, our results support the hypothesis that a subcortical pathway to the amygdala plays a role in rapid sensory processing of faces, in particular during early stimulus processing. This finding contributes to an understanding of the amygdala as a behavioural relevance detector

The neural architecture of compositional generalization

The ability to generalize previously learned knowledge to novel situations is essential for adaptive behavior. To investigate the neural mechanisms underlying the ability to infer novel compositional word meanings, we developed a behavioral paradigm to probe compositional inference in language. Participants were trained on the meanings of compositional words made up of known stems (“good”) and novel affixes (“kla”) from an artificial language. The meaning of the compositional words depended on the position of the novel affix (“goodkla = bad”, “klahorse = pony”). We then asked participants to infer the meaning of novel compositional words (“whitekla =?”, “klacat =?”) that were either congruent or incongruent with the established rule (“klawhite” is incongruent because a small version of “white” does not exist). During fMRI, participants performed a semantic priming task in which the novel words served as either congruent or incongruent primes (“whitekla”) and their synonyms (“black”) served as targets. Our results demonstrated that participants were able to generate novel compositional meanings on the fly, successfully inferring meanings of congruent versus incongruent words. Univariate analysis of fMRI data at target words revealed a greater repetition suppression effect when primed with congruent than incongruent words in the left inferior frontal gyrus, which suggests that novel meanings are derived at this linguistic “building” hub. Further analysis of congruent versus incongruent prime-related activity revealed a broad frontal-parietal network, including the hippocampus, a brain area commonly associated with the generalization process of structural relationships. Furthermore, we employed multivariate representational similarity analysis to demonstrate structural rule and word meaning representations in hippocampus and left-lateralized core language areas. Together, these findings suggest that compositional generalization in language recruits a domain-general network shared with action planning, compositional vision and constructive relational memory, while newly inferred meanings are represented in more language-specific regions.</p

Grid-like entorhinal representation of an abstract value space during prospective decision making

Abstract How valuable a choice option is often changes over time, making the prediction of value changes an important challenge for decision making. Prior studies identified a cognitive map in the hippocampal-entorhinal system that encodes relationships between states and enables prediction of future states, but does not inherently convey value during prospective decision making. In this fMRI study, participants predicted changing values of choice options in a sequence, forming a trajectory through an abstract two-dimensional value space. During this task, the entorhinal cortex exhibited a grid-like representation with an orientation aligned to the axis through the value space most informative for choices. A network of brain regions, including ventromedial prefrontal cortex, tracked the prospective value difference between options. These findings suggest that the entorhinal grid system supports the prediction of future values by representing a cognitive map, which might be used to generate lower-dimensional value signals to guide prospective decision making