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.

Spectral pattern similarity analysis: Tutorial and application in developmental cognitive neuroscience.

The human brain encodes information in neural activation patterns. While standard approaches to analyzing neural data focus on brain (de-)activation (e.g., regarding the location, timing, or magnitude of neural responses), multivariate neural pattern similarity analyses target the informational content represented by neural activity. In adults, a number of representational properties have been identified that are linked to cognitive performance, in particular the stability, distinctiveness, and specificity of neural patterns. However, although growing cognitive abilities across childhood suggest advancements in representational quality, developmental studies still rarely utilize information-based pattern similarity approaches, especially in electroencephalography (EEG) research. Here, we provide a comprehensive methodological introduction and step-by-step tutorial for pattern similarity analysis of spectral (frequency-resolved) EEG data including a publicly available pipeline and sample dataset with data from children and adults. We discuss computation of single-subject pattern similarities and their statistical comparison at the within-person to the between-group level as well as the illustration and interpretation of the results. This tutorial targets both novice and more experienced EEG researchers and aims to facilitate the usage of spectral pattern similarity analyses, making these methodologies more readily accessible for (developmental) cognitive neuroscientists.

Contributions of representational distinctiveness and stability to memory performance and age differences.

Long-standing theories of cognitive aging suggest that memory decline is associated with age-related differences in the way information is neurally represented. Multivariate pattern similarity analyses enabled researchers to take a representational perspective on brain and cognition, and allowed them to study the properties of neural representations that support successful episodic memory. Two representational properties have been identified as crucial for memory performance, namely the distinctiveness and the stability of neural representations. Here, we review studies that used multivariate analysis tools for different neuroimaging techniques to clarify how these representational properties relate to memory performance across adulthood. While most evidence on age differences in neural representations involved stimulus category information , recent studies demonstrated that particularly item-level stability and specificity of activity patterns are linked to memory success and decline during aging. Overall, multivariate methods offer a versatile tool for our understanding of age differences in the neural representations underlying memory.

Memory specificity is linked to repetition effects in event-related potentials across the lifespan.

The specificity with which past experiences can be remembered varies across the lifespan, possibly due to differences in how precisely information is encoded. Memory formation can be investigated through repetition effects, the common finding that neural activity is altered when stimuli are repeated. However, whether differences in this indirect measure of memory formation relate to lifespan differences in memory specificity has not yet been established. In the present study, we examined repetition effects in event-related potentials and their relation to recognition. During incidental encoding, children (aged 7-9 years), young adults (18-30 years), and older adults (65-76 years) viewed repeated object images from different categories. During subsequent recognition, we distinguished memory for the specific items versus the general categories. We identified repetition suppression in all age groups, and repetition enhancement for adults. Furthermore, individual item recognition performance comprising lure discrimination was positively associated with the magnitude of the neural repetition effects, which did not differ between groups, indicating common neural mechanisms of memory formation. Our findings demonstrate that neural repetition effects reflect the formation of highly specific memory representations and highlight their significance as a neural indicator of individual differences in episodic memory encoding across the lifespan.

Tracking Age Differences in Neural Distinctiveness across Representational Levels.

The distinctiveness of neural information representation is crucial for successful memory performance but declines with advancing age. Computational models implicate age-related neural dedifferentiation on the level of item representations, but previous studies mostly focused on age differences of categorical information representation in higher-order visual regions. In an age-comparative fMRI study, we combined univariate analyses and whole-brain searchlight pattern similarity analyses to elucidate age differences in neural distinctiveness at both category and item levels and their relation to memory. Thirty-five younger (18-27 years old) and 32 older (67-75 years old) women and men incidentally encoded images of faces and houses, followed by an old/new recognition memory task. During encoding, age-related neural dedifferentiation was shown as reduced category-selective processing in ventral visual cortex and impoverished item specificity in occipital regions. Importantly, successful subsequent memory performance built on high item stability, that is, high representational similarity between initial and repeated presentation of an item, which was greater in younger than older adults. Overall, we found that differences in representational distinctiveness coexist across representational levels and contribute to interindividual and intraindividual variability in memory success, with item specificity being the strongest contributor. Our results close an important gap in the literature, showing that older adults' neural representation of item-specific information in addition to categorical information is reduced compared with younger adults.SIGNIFICANCE STATEMENT A long-standing hypothesis links age-related cognitive decline to a loss of neural specificity. While previous evidence supports the notion of age-related neural dedifferentiation of category-level information in ventral visual cortex, whether or not age differences exist at the item level was a matter of debate. Here, we observed age group differences at both levels as well as associations between both categorical distinctiveness and item specificity to memory performance, with item specificity being the strongest contributor. Importantly, age differences in occipital item specificity were largely due to reduced item stability across repetitions in older adults. Our results suggest that age differences in neural representations can be observed across the entire cortical hierarchy and are not limited to category-level information.

Neural Pattern Similarity Differentially Relates to Memory Performance in Younger and Older Adults.

Age-related memory decline is associated with changes in neural functioning, but little is known about how aging affects the quality of information representation in the brain. Whereas a long-standing hypothesis of the aging literature links cognitive impairments to less distinct neural representations in old age ("neural dedifferentiation"), memory studies have shown that overlapping neural representations of different studied items are beneficial for memory performance. In an electroencephalography (EEG) study, we addressed the question whether distinctiveness or similarity between patterns of neural activity supports memory differentially in younger and older adults. We analyzed between-item neural pattern similarity in 50 younger (19-27 years old) and 63 older (63-75 years old) male and female human adults who repeatedly studied and recalled scene-word associations using a mnemonic imagery strategy. We compared the similarity of spatiotemporal EEG frequency patterns during initial encoding in relation to subsequent recall performance. The within-person association between memory success and pattern similarity differed between age groups: For older adults, better memory performance was linked to higher similarity early in the encoding trials, whereas young adults benefited from lower similarity between earlier and later periods during encoding, which might reflect their better success in forming unique memorable mental images of the joint picture-word pairs. Our results advance the understanding of the representational properties that give rise to subsequent memory, as well as how these properties may change in the course of aging.SIGNIFICANCE STATEMENT Declining memory abilities are one of the most evident limitations for humans when growing older. Despite recent advances of our understanding of how the brain represents and stores information in distributed activation patterns, little is known about how the quality of information representation changes during aging and thus affects memory performance. We investigated how the similarity between neural representations relates to subsequent memory in younger and older adults. We present novel evidence that the interaction of pattern similarity and memory performance differs between age groups: Older adults benefited from higher similarity during early encoding, whereas young adults benefited from lower similarity between early and later encoding. These results provide insights into the nature of memory and age-related memory deficits.

Hearing Scenes: A Neuromagnetic Signature of Auditory Source and Reverberant Space Separation.

Perceiving the geometry of surrounding space is a multisensory process, crucial to contextualizing object perception and guiding navigation behavior. Humans can make judgments about surrounding spaces from reverberation cues, caused by sounds reflecting off multiple interior surfaces. However, it remains unclear how the brain represents reverberant spaces separately from sound sources. Here, we report separable neural signatures of auditory space and source perception during magnetoencephalography (MEG) recording as subjects listened to brief sounds convolved with monaural room impulse responses (RIRs). The decoding signature of sound sources began at 57 ms after stimulus onset and peaked at 130 ms, while space decoding started at 138 ms and peaked at 386 ms. Importantly, these neuromagnetic responses were readily dissociable in form and time: while sound source decoding exhibited an early and transient response, the neural signature of space was sustained and independent of the original source that produced it. The reverberant space response was robust to variations in sound source, and vice versa, indicating a generalized response not tied to specific source-space combinations. These results provide the first neuromagnetic evidence for robust, dissociable auditory source and reverberant space representations in the human brain and reveal the temporal dynamics of how auditory scene analysis extracts percepts from complex naturalistic auditory signals.

Semi-automatic lung segmentation of DCE-MRI data sets of 2-year old children after congenital diaphragmatic hernia repair: Initial results.

In congenital diaphragmatic hernia (CDH), lung hypoplasia and secondary pulmonary hypertension are the major causes of death and severe disability. Based on new therapeutic strategies survival rates could be improved to up to 80%. However, after surgical repair of CDH, long-term follow-up of these pediatric patients is necessary. In this, dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) provides insights into the pulmonary microcirculation and might become a tool within the routine follow-up program of CDH patients. However, whole lung segmentation from DCE-MRI scans is tedious and automated procedures are warranted. Therefore, in this study, an approach to semi-automated lung segmentation is presented. Segmentation of the lung is obtained by calculating the cross correlation and the area under curve between all voxels in the data set and a reference region-of-interest (ROI), here the arterial input function (AIF). By applying an upper and lower threshold to the obtained maps and intersecting these, a final segmentation is reached. This approach was tested on twelve DCE-MRI data sets of 2-year old children after CDH repair. Segmentation accuracy was evaluated by comparing obtained automatic segmentations to manual delineations using the Dice overlap measure. Optimal thresholds for the cross correlation were 0.5/0.95 and 0.1/0.5 for the area under curve, respectively. The ipsilateral (left) lung showed reduced segmentation accuracy compared to the contralateral (right) lung. Average processing time was about 1.4s per data set. Average Dice score was 0.7±0.1 for the whole lung. In conclusion, initial results are promising. By our approach, whole lung segmentation is possible and a rapid evaluation of whole lung perfusion becomes possible. This might allow for a more detailed analysis of lung hypoplasia of children after CDH.