The Neural Representation of Binaural Sound Localization Cues Across Different Subregions of the Chicken's Inferior Colliculus.

The sound localization behavior of the nocturnally hunting barn owl and its underlying neural computations is a textbook example of neuroethology. Differences in sound timing and level at the two ears are integrated in a series of well-characterized steps, from brainstem to inferior colliculus (IC), resulting in a topographical neural representation of auditory space. It remains an important question of brain evolution: How is this specialized case derived from a more plesiomorphic pattern? The present study is the first to match physiology and anatomical subregions in the non-owl avian IC. Single-unit responses in the chicken IC were tested for selectivity to different frequencies and to the binaural difference cues. Their anatomical origin was reconstructed with the help of electrolytic lesions and immunohistochemical identification of different subregions of the IC, based on previous characterizations in owl and chicken. In contrast to barn owl, there was no distinct differentiation of responses in the different subregions. We found neural topographies for both binaural cues but no evidence for a coherent representation of auditory space. The results are consistent with previous work in pigeon IC and chicken higher-order midbrain and suggest a plesiomorphic condition of multisensory integration in the midbrain that is dominated by lateral panoramic vision.

Early visual cortices reveal interrelated item and category representations in aging.

Neural dedifferentiation, the finding that neural representations tend to be less distinct in older adults compared with younger adults, has been associated with age-related declines in memory performance. Most studies assessing the relation between memory and neural dedifferentiation have evaluated how age impacts the distinctiveness of neural representations for different visual categories (e.g., scenes and objects). However, how age impacts the quality of neural representations at the level of individual items is still an open question. Here, we present data from an age-comparative fMRI study that aimed to understand how the distinctiveness of neural representations for individual stimuli differs between younger and older adults and relates to memory outcomes. Pattern similarity searchlight analyses yielded indicators of neural dedifferentiation at the level of individual items as well as at the category level in posterior occipital cortices. We asked whether age differences in neural distinctiveness at each representational level were associated with inter- and/or intraindividual variability in memory performance. While age-related dedifferentiation at both the item and category level related to between-person differences in memory, neural distinctiveness at the category level also tracked within-person variability in memory performance. Concurrently, neural distinctiveness at the item level was strongly associated with neural distinctiveness at the category level both within and across participants, elucidating a potential representational mechanism linking item- and category-level distinctiveness. In sum, we provide evidence that age-related neural dedifferentiation co-exists across multiple representational levels and is related to memory performance.Significance Statement Age-related memory decline has been associated with neural dedifferentiation, the finding that older adults have less distinctive neural representations than younger adults. This has been mostly shown for category information, while evidence for age differences in the specificity of item representations is meager. We used pattern similarity searchlight analyses to find indicators of neural dedifferentiation at both levels of representation (category and item) and linked distinctiveness to memory performance. Both item- and category-level dedifferentiation in the calcarine cortex were related to interindividual differences in memory performance, while category-level distinctiveness further tracked intraindividual variability. Crucially, neural distinctiveness was strongly tied between the item and category levels, indicating that intersecting representational properties of posterior occipital cortices reflect both individual exemplars and categories.

Age differences in functional connectivity track dedifferentiation of category representations.

With advancing age, the distinctiveness of neural representations of information declines. While the finding of this so-called 'age-related neural dedifferentiation' in category-selective neural regions is well-described, the contribution of age-related changes in network organization to dedifferentiation is unknown. Here, we asked whether age differences in a) whole-brain network segregation (i.e., network dedifferentiation) and b) functional connectivity to category-selective neural regions contribute to regional dedifferentiation of categorical representations. Younger and older adults viewed blocks of face and house stimuli in the fMRI scanner. We found an age-related decline in neural distinctiveness for faces in the fusiform gyrus (FG) and for houses in the parahippocampal gyrus (PHG). Functional connectivity analyses revealed age-related dedifferentiation of global network structure as well as age differences in connectivity between the FG and early visual cortices. Interindividual correlations demonstrated that regional distinctiveness was related to network segregation as well as connectivity of the FG to the visual network. Together, our findings reveal that dedifferentiation of categorical representations may be linked to age-related reorganization of functional networks.

Age differences in neural distinctiveness during memory encoding, retrieval, and reinstatement.

Robust evidence points to mnemonic deficits in older adults related to dedifferentiated, i.e. less distinct, neural responses during memory encoding. However, less is known about retrieval-related dedifferentiation and its role in age-related memory decline. In this study, younger and older adults were scanned both while incidentally learning face and house stimuli and while completing a surprise recognition memory test. Using pattern similarity searchlight analyses, we looked for indicators of neural dedifferentiation during encoding, retrieval, and encoding-retrieval reinstatement. Our findings revealed age-related reductions in neural distinctiveness during all memory phases in visual processing regions. Interindividual differences in retrieval- and reinstatement-related distinctiveness were strongly associated with distinctiveness during memory encoding. Both item- and category-level distinctiveness predicted trial-wise mnemonic outcomes. We further demonstrated that the degree of neural distinctiveness during encoding tracked interindividual variability in memory performance better than both retrieval- and reinstatement-related distinctiveness. All in all, we contribute to meager existing evidence for age-related neural dedifferentiation during memory retrieval. We show that neural distinctiveness during retrieval is likely tied to recapitulation of encoding-related perceptual and mnemonic processes.

Age-related declines in neural selectivity manifest differentially during encoding and recognition.

One important factor contributing to age-related memory decline is the loss of distinctiveness with which information is represented in brain activity. This loss in neural selectivity may be driven by neural attenuation (i.e., reduced activation to target stimuli) or neural broadening (i.e., increased activation to nontarget stimuli). In this fMRI study, we assessed age differences in neural selectivity during first encoding, repeated encoding, and recognition, as well as the underlying pattern (broadening vs. attenuation). We found lower neural selectivity in older compared to younger adults during all memory stages. Crucially, while reduced selectivity in older adults was due to neural broadening during first encoding, it was driven by neural attenuation during recognition, but revealed no clear pattern during repeated encoding. Our findings suggest that intrinsic differences between memory stages may interact with neural activity to manifest as either neural broadening or attenuation. Moreover, despite these differential patterns, neural selectivity was highly correlated across memory stages, indicating that one common mechanism may underly distinct expressions of age-related neural dedifferentiation.

Investigating Differences in Behavior and Brain in Human-Human and Human-Autonomous Vehicle Interactions in Time-Critical Situations.

Some studies provide evidence that humans could actively exploit the alleged technological advantages of autonomous vehicles (AVs). This implies that humans may tend to interact differently with AVs as compared to human driven vehicles (HVs) with the knowledge that AVs are programmed to be risk-averse. Hence, it is important to investigate how humans interact with AVs in complex traffic situations. Here, we investigated whether participants would value interactions with AVs differently compared to HVs, and if these differences can be characterized on the behavioral and brain-level. We presented participants with a cover story while recording whole-head brain activity using fNIRS that they were driving under time pressure through urban traffic in the presence of other HVs and AVs. Moreover, the AVs were programmed defensively to avoid collisions and had faster braking reaction times than HVs. Participants would receive a monetary reward if they managed to finish the driving block within a given time-limit without risky driving maneuvers. During the drive, participants were repeatedly confronted with left-lane turning situations at unsignalized intersections. They had to stop and find a gap to turn in front of an oncoming stream of vehicles consisting of HVs and AVs. While the behavioral results did not show any significant difference between the safety margin used during the turning maneuvers with respect to AVs or HVs, participants tended to be more certain in their decision-making process while turning in front of AVs as reflected by the smaller variance in the gap size acceptance as compared to HVs. Importantly, using a multivariate logistic regression approach, we were able to predict whether the participants decided to turn in front of HVs or AVs from whole-head fNIRS in the decision-making phase for every participant (mean accuracy = 67.2%, SD = 5%). Channel-wise univariate fNIRS analysis revealed increased brain activation differences for turning in front of AVs compared to HVs in brain areas that represent the valuation of actions taken during decision-making. The insights provided here may be useful for the development of control systems to assess interactions in future mixed traffic environments involving AVs and HVs.