Similarity Of Activity Patterns Research Articles

Ámbito de hogar, preferencia de hábitat y patrones de actividad del zorro de Sechura Lycalopex sechurae (Mammalia: Canidae) en el Desierto de Sechura, noroeste del Perú

The Sechura fox (Lycalopex sechurae) is a little-studied species despite being common in northwestern Peru and listed as Near Threatened internationally. This study presents the home range, habitat preference, and activity patterns of L. sechurae in two locations of the Sechura Desert: The Mangroves of San Pedro de Vice (MSPV) and the Illescas National Reserve (RNI). Using GPS collars, the minimum convex polygon method, and the Kernel estimator (KE), the home range of four female individuals (two from each site) was calculated. Additionally, the GPS location data were used to estimate activity patterns and habitat preferences for each individual. The home range of females from MSPV was 0.6 and 1 km² (95% KE), whereas, for the RNI, it was 3.5 and 25.1 km² (95% KE). Females from MSPV preferred dry forest (54.8% and 76.1%), while those from RNI favored desert scrub (64.3% and 64.5%). All individuals exhibited cathemeral behavior, with increased nocturnal activity. Our results demonstrate variability in home range sizes, similarity in activity patterns compared to other studies, and highlight the importance of dry forest and desert scrub as resource-rich habitats for Lycalopex sechurae.

Subsequent Memory Effects in Cortical Pattern Similarity Differ by Semantic Class.

Although living and nonliving stimuli are known to rely on distinct brain regions during perception, it is largely unknown if their episodic memory encoding mechanisms differ as well. To investigate this issue, we asked participants to encode object pictures (e.g., a picture of a tiger) and to retrieve them later in response to their names (e.g., word "tiger"). For each of four semantic classes (living-animate, living-inanimate, nonliving-large, and nonliving-small), we examined differences in the similarity in activation patterns (neural pattern similarity [NPS]) for subsequently remembered versus forgotten items. Higher NPS for remembered items suggests an advantage of within-class item similarity, whereas lower NPS for remembered items indicates an advantage for item distinctiveness. We expect NPS within class-specific regions to be higher for remembered than for forgotten items. For example, the parahippocampal cortex has a well-known role in scene processing [Aminoff, E. M., Kveraga, K., & Bar, M. The role of the parahippocampal cortex in cognition. Trends in Cognitive Sciences, 17, 379-390, 2013], and the anterior temporal and inferior frontal gyrus have well-known roles in object processing [Clarke, A., & Tyler, L. K. Object-specific semantic coding in human perirhinal cortex. Journal of Neuroscience, 34, 4766-4775, 2014]. As such, we expect to see higher NPS for remembered items in these regions pertaining to scenes and objects, respectively. Consistent with this hypothesis, in fusiform, parahippocampal, and retrosplenial regions, higher NPS predicted memory for subclasses of nonliving objects, whereas in the left inferior frontal and left retrosplenial regions, lower NPS predicted memory for subclasses of living objects. Taken together, the results support the idea that subsequent memory depends on a balance of similarity and distinctiveness and demonstrate that the neural mechanisms of episodic encoding differ across semantic categories.

Cortical changes during the learning of sequences of simultaneous finger presses

Abstract The cortical alterations underpinning the acquisition of motor skills remain debated. In this longitudinal study in younger adults, we acquired performance and neuroimaging (7 T MRI) measures weekly over the course of 6 weeks to investigate neural changes associated with learning sequences of simultaneous finger presses executed with the non-dominant hand. Both the intervention group (n = 33), which practiced the finger sequences at home, and the control group (n = 30, no home practice) showed general performance improvements, but performance improved more and became more consistent for sequences that were intensively trained by the intervention group, relative to those that were not. Brain activity for trained sequences decreased compared with untrained sequences in the bilateral parietal and premotor cortices. No training-related changes in the primary sensorimotor areas were detected. The similarity of activation patterns between trained and untrained sequences decreased in secondary, but not primary, sensorimotor areas, while the similarity of the activation patterns between different trained sequences did not show reliable changes. Neither the variability of activation patterns across trials, nor the estimates of brain structure displayed practice-related changes that reached statistical significance. Overall, the main correlate of learning configural sequences was a reduction in brain activity in secondary motor areas.

Independency of Coding for Affective Similarities and for Word Co-occurrences in Temporal Perisylvian Neocortex.

Word valence is one of the principal dimensions in the organization of word meaning. Co-occurrence-based similarities calculated by predictive natural language processing models are relatively poor at representing affective content, but very powerful in their own way. Here, we determined how these two canonical but distinct ways of representing word meaning relate to each other in the human brain both functionally and neuroanatomically. We re-analysed an fMRI study of word valence. A co-occurrence-based model was used and the correlation with the similarity of brain activity patterns was compared to that of affective similarities. The correlation between affective and co-occurrence-based similarities was low (r = 0.065), confirming that affect was captured poorly by co-occurrence modelling. In a whole-brain representational similarity analysis, word embedding similarities correlated significantly with the similarity between activity patterns in a region confined to the superior temporal sulcus to the left, and to a lesser degree to the right. Affective word similarities correlated with the similarity in activity patterns in this same region, confirming previous findings. The affective similarity effect extended more widely beyond the superior temporal cortex than the effect of co-occurrence-based similarities did. The effect of co-occurrence-based similarities remained unaltered after partialling out the effect of affective similarities (and vice versa). To conclude, different aspects of word meaning, derived from affective judgements or from word co-occurrences, are represented in superior temporal language cortex in a neuroanatomically overlapping but functionally independent manner.

Analyzing travel mobility patterns in city destinations: Implications for destination design

Understanding the features of travel activities is important in elaborating travel behaviors and segmenting travelers based on the similarity of activity patterns. This research applying mobile big data analytics suggests a novel method to classify travelers by considering the sequences of travel activity with individuals' trajectories. The result revealed five distinct travel types visiting city destinations and demonstrated dynamic travel flow among different mobility types. Recognizing that different types of travel patterns present important information in understanding destinations’ roles (or functions), this study attempts to characterize the functionality dynamics of city destinations based on travel activity types. As a result, the findings of this research provide insights into the demand-driven construct (or flow-based) of destination planning, which is the foundation of smart destination design. In addition, important methodological and practical implications that could be useful for city destination planners/designers are suggested.

Local similarity of activity patterns during auditory and visual processing

Neuroimaging studies have shown that brain activity is variable and changes according to stimuli and the environmental context, reflecting brain coding or information representations at different processing levels. However, little is known about activity organization that reflects coding strategies. Here, we explored and compared two different coding approaches, spatial via cross-correlation and intensity-based coding using mutual information. Using two fMRI datasets and different seeds, we searched for the spatial and intensity-based similarities with the seeds in brain activity. Our results showed that, apart from the seed regions, significant regions detected by intensity-based similarity analysis differ completely from those found using cross-correlation. These findings may indicate that information shared through spatial coding differs from that transmitted via non-spatial coding processes. Our results suggest that brain coding is organized in several different ways to optimize information processing.

Context free and context-dependent conceptual representation in the brain.

How concepts are coded in the brain is a core issue in cognitive neuroscience. Studies have focused on how individual concepts are processed, but the way in which conceptual representation changes to suit the context is unclear. We parametrically manipulated the association strength between words, presented in pairs one word at a time using a slow event-related fMRI design. We combined representational similarity analysis and computational linguistics to probe the neurocomputational content of these trials. Individual word meaning was maintained in supramarginal gyrus (associated with verbal short-term memory) when items were judged to be unrelated, but not when a linking context was retrieved. Context-dependent meaning was instead represented in left lateral prefrontal gyrus (associated with controlled retrieval), angular gyrus, and ventral temporal lobe (regions associated with integrative aspects of memory). Analyses of informational connectivity, examining the similarity of activation patterns across trials between sites, showed that control network regions had more similar multivariate responses across trials when association strength was weak, reflecting a common controlled retrieval state when the task required more unusual associations. These findings indicate that semantic control and representational sites amplify contextually relevant meanings in trials judged to be related.

Influence of target-distractor neural similarity on working memory performance in older and younger adults

ABSTRACT According to the inhibitory deficit hypothesis, older adults often fail to selectively inhibit distractors and attend to relevant information in working memory, leading to poorer memory of target items but better recall of irrelevant distractors compared to younger adults. Here, we explored how neural similarity of activity patterns between relevant and irrelevant stimulus categories impacts memory performance. We found evidence that older adults may benefit from failing to inhibit distractors that are similar to targets, perhaps because sustained neural activation of distractors partially supports maintenance of targets when they share neural resources, allowing for better subsequent recognition of studied target items. We also found increased category-specific multivoxel pattern activity in medial temporal regions in younger compared to older adults as category similarity increased. We propose that this reduced category-specific activation in medial temporal regions in older adults may reflect more blended representations of all the information available in working memory.

Spatial Bayesian GLM on the cortical surface produces reliable task activations in individuals and groups

The general linear model (GLM) is a widely popular and convenient tool for estimating the functional brain response and identifying areas of significant activation during a task or stimulus. However, the classical GLM is based on a massive univariate approach that does not explicitly leverage the similarity of activation patterns among neighboring brain locations. As a result, it tends to produce noisy estimates and be underpowered to detect significant activations, particularly in individual subjects and small groups. A recently proposed alternative, a cortical surface-based spatial Bayesian GLM, leverages spatial dependencies among neighboring cortical vertices to produce more accurate estimates and areas of functional activation. The spatial Bayesian GLM can be applied to individual and group-level analysis. In this study, we assess the reliability and power of individual and group-average measures of task activation produced via the surface-based spatial Bayesian GLM. We analyze motor task data from 45 subjects in the Human Connectome Project (HCP) and HCP Retest datasets. We also extend the model to multi-run analysis and employ subject-specific cortical surfaces rather than surfaces inflated to a sphere for more accurate distance-based modeling. Results show that the surface-based spatial Bayesian GLM produces highly reliable activations in individual subjects and is powerful enough to detect trait-like functional topologies. Additionally, spatial Bayesian modeling enhances reliability of group-level analysis even in moderately sized samples (n=45). Notably, the power of the spatial Bayesian GLM to detect activations above a scientifically meaningful effect size is nearly invariant to sample size, exhibiting high power even in small samples (n=10). The spatial Bayesian GLM is computationally efficient in individuals and groups and is convenient to implement with the open-source BayesfMRI R package.

Orienting to different dimensions of word meaning alters the representation of word meaning in early processing regions.

Conscious processing of word meaning can be guided by attention. In this event-related functional magnetic resonance imaging study in 22 healthy young volunteers, we examined in which regions orienting attention to two fundamental and generic dimensions of word meaning, concreteness versus valence, alters the semantic representations coded in activity patterns. The stimuli consisted of 120 nouns in written or spoken modality which varied factorially along the concreteness and valence axis. Participants performed a forced-choice judgement of either concreteness or valence. Rostral and subgenual anterior cingulate were strongly activated during valence judgement, and precuneus and the dorsal attention network during concreteness judgement. Task and stimulus type interacted in right posterior fusiform gyrus, left lingual gyrus, precuneus, and insula. In the right posterior fusiform gyrus and the left lingual gyrus, the correlation between the pairwise similarity in activity patterns evoked by words and the pairwise distance in valence and concreteness was modulated by the direction of attention, word valence or concreteness. The data indicate that orienting attention to basic dimensions of word meaning exerts effects on the representation of word meaning in more peripheral nodes, such as the ventral occipital cortex, rather than the core perisylvian language regions.

Homogenization of face neural representation during development

Extensive studies have demonstrated that face processing ability develops gradually during development until adolescence. However, the underlying mechanism is unclear. One hypothesis is that children and adults represent faces in qualitatively different fashions with different group templates. An alternative hypothesis emphasizes the development as a quantitative change with a decrease of variation in representations. To test these hypotheses, we used between-participant correlation to measure activation pattern similarity both within and between late-childhood children and adults. We found that activation patterns for faces in the fusiform face area and occipital face area were less similar within the children group than within the adults group, indicating children had a greater variation in representing faces. Interestingly, the activation pattern similarity of children to their own group template was not significantly larger than that to adults’ template, suggesting children and adults shared a template in representing faces. Further, the decrease in representation variance was likely a general principle in the ventral visual cortex, as a similar result was observed in a scene-selective region when perceiving scenes. Taken together, our study provides evidence that development of object representation may result from a homogenization process that shifts from greater variance in late-childhood to homogeneity in adults.

Age-related declines in neural distinctiveness correlate across brain areas and result from both decreased reliability and increased confusability

ABSTRACT According to the neural dedifferentiation hypothesis, age-related reductions in the distinctiveness of neural representations contribute to sensory, cognitive, and motor declines associated with aging: neural activity associated with different stimulus categories becomes more confusable with age and behavioral performance suffers as a result. Initial studies investigated age-related dedifferentiation in the visual cortex, but subsequent research has revealed declines in other brain regions, suggesting that dedifferentiation may be a general feature of the aging brain. In the present study, we used functional magnetic resonance imaging to investigate age-related dedifferentiation in the visual, auditory, and motor cortices. Participants were 58 young adults and 79 older adults. The similarity of activation patterns across different blocks of the same category was calculated (within-category correlation, a measure of reliability) as was the similarity of activation patterns elicited by different categories (between-category correlations, a measure of confusability). Neural distinctiveness was defined as the difference between the mean within- and between-category similarity. We found age-related reductions in neural distinctiveness in the visual, auditory, and motor cortices, which were driven by both decreases in within-category similarity and increases in between-category similarity. There were significant positive cross-region correlations between neural distinctiveness in different regions. These correlations were driven by within-category similarities, a finding that indicates that declines in the reliability of neural activity appear to occur in tandem across the brain. These findings suggest that the changes in neural distinctiveness that occur in healthy aging result from changes in both the reliability and confusability of patterns of neural activity.

Active Sense: Early Staging of Non-Insulin Dependent Diabetes Mellitus (NIDDM) Hinges upon Recognizing Daily Activity Pattern

The Human Activity Recognition (HAR) system allows various accessible entries for the early diagnosis of Diabetes as one of the nescient applications domains for the HAR. Long Short-Term Memory (LSTM) was applied and recognized 13 activities that resemble diabetes symptoms. Afterward, risk factor assessment for an experimental subject identified similar activity pattern attributes between diabetic patients and the experimental subject. Because of this, a trained LSTM model was deployed to monitor the average time length for every activity performed by the experimental subject for 30 consecutive days. Concurrently, the symptomatic diabetes activity patterns of diabetic patients were explored. The cosine similarity of activity patterns of the experimental subject and diabetic patients measured 57.39%, putting the experimental subject into moderate risk factor class. The experimental subject was clinically tested for risk factors using the diabetic clinical diagnosis process, known as the A1C. The A1C level was 6.1%, recognizing the experimental subject as a patient suffering from Diabetes. Thus, the proposed novel approach remarkably classifies the risk factor level based on activity patterns.

Frontoparietal pattern similarity analyses of cognitive control in monozygotic twins

The ability to flexibly adapt thoughts and actions in a goal-directed manner appears to rely on cognitive control mechanisms that are strongly impacted by individual differences. A powerful research strategy for investigating the nature of individual variation is to study monozygotic (identical) twins. Evidence of twin effects have been observed in prior behavioral and neuroimaging studies, yet within the domain of cognitive control, it remains to be demonstrated that the neural underpinnings of such effects are specific and reliable. Here, we utilize a multi-task, within-subjects event-related neuroimaging design with functional magnetic resonance imaging to investigate twin effects through multivariate pattern similarity analyses. We focus on fronto-parietal brain regions exhibiting consistently increased activation associated with cognitive control demands across four task domains: selective attention, context processing, multi-tasking, and working memory. Healthy young adult monozygotic twin pairs exhibited increased similarity of within- and cross-task activation patterns in these fronto-parietal regions, relative to unrelated pairs. Twin activation pattern similarity effects were clearest under high control demands, were not present in a set of task-unrelated parcels or due to anatomic similarity, and were primarily observed during the within-trial timepoints in which the control demands peaked. Together, these results indicate that twin similarity in the neural representation of cognitive control may be domain-general but also functionally and temporally specific in relation to the level of control demand. The findings suggest a genetic and/or environmental basis for individual variation in cognitive control function, and highlight the potential of twin-based neuroimaging designs for exploring heritability questions within this domain.

Representation of social content in dorsomedial prefrontal cortex underlies individual differences in agreeableness trait

Personality traits reflect key aspects of individual variability in different psychological domains. Understanding the mechanisms that give rise to these differences requires an exhaustive investigation of the behaviors associated with such traits, and their underlying neural sources. Here we investigated the mechanisms underlying agreeableness, one of the five major dimensions of personality, which has been linked mainly to socio-cognitive functions. In particular, we examined whether individual differences in the neural representations of social information are related to differences in agreeableness of individuals. To this end, we adopted a multivariate representational similarity approach that captured within single individuals the activation pattern similarity of social and non-social content, and tested its relation to the agreeableness trait in a hypothesis-driven manner. The main result confirmed our prediction: processing social and non-social content led to similar patterns of activation in individuals with low agreeableness, while in more agreeable individuals these patterns were more dissimilar. Critically, this association between agreeableness and encoding similarity of social and random content was significant only in the dorsomedial prefrontal cortex, a brain region consistently involved during attributions of mental states. The present finding reveals the link between neural mechanisms underlying social information processing and agreeableness, a personality trait highly related to socio-cognitive abilities, thereby providing a step forward in characterizing its neural determinants. Furthermore, it emphasizes the advantage of multivariate pattern analysis approaches in capturing and understanding the neural sources of individual variations.

Representation of associative and affective semantic similarity of abstract words in the lateral temporal perisylvian language regions

The examination of semantic cognition has traditionally identified word concreteness as well as valence as two of the principal dimensions in the representation of conceptual knowledge. More recently, corpus-based vector space models as well as graph-theoretical analysis of large-scale task-related behavioural responses have revolutionized our insight into how the meaning of words is structured. In this fMRI study, we apply representational similarity analysis to investigate the conceptual representation of abstract words. Brain activity patterns were related to a cued-association based graph as well as to a vector-based co-occurrence model of word meaning. Twenty-six subjects (19 females and 7 males) performed an overt repetition task during fMRI. First, we performed a searchlight classification procedure to identify regions where activity is discriminable between abstract and concrete words. These regions were left inferior frontal gyrus, the upper and lower bank of the superior temporal sulcus bilaterally, posterior middle temporal gyrus and left fusiform gyrus. Representational Similarity Analysis demonstrated that for abstract words, the similarity of activity patterns in the cortex surrounding the superior temporal sulcus bilaterally and in the left anterior superior temporal gyrus reflects the similarity in word meaning. These effects were strongest for semantic similarity derived from the cued association-based graph and for affective similarity derived from either of the two models. The latter effect was mainly driven by positive valence words. This research highlights the close neurobiological link between the information structure of abstract and affective word content and the similarity in activity pattern in the lateral and anterior temporal language system.

Pattern Similarity Analyses of FrontoParietal Task Coding: Individual Variation and Genetic Influences.

Pattern similarity analyses are increasingly used to characterize coding properties of brain regions, but relatively few have focused on cognitive control processes in FrontoParietal regions. Here, we use the Human Connectome Project (HCP) N-back task functional magnetic resonance imaging (fMRI) dataset to examine individual differences and genetic influences on the coding of working memory load (0-back, 2-back) and perceptual category (Face, Place). Participants were grouped into 105 monozygotic twin, 78 dizygotic twin, 99 nontwin sibling, and 100 unrelated pairs. Activation pattern similarity was used to test the hypothesis that FrontoParietal regions would have higher similarity for same load conditions, while Visual regions would have higher similarity in same perceptual category conditions. Results confirmed this highly robust regional double dissociation in neural coding, which also predicted individual differences in behavioral performance. In pair-based analyses, anatomically selective genetic relatedness effects were observed: relatedness predicted greater activation pattern similarity in FrontoParietal only for load coding and in Visual only for perceptual coding. Further, in related pairs, the similarity of load coding in FrontoParietal regions was uniquely associated with behavioral performance. Together, these results highlight the power of task fMRI pattern similarity analyses for detecting key coding and heritability features of brain regions.

A Novel 2D Standard Cartesian Representation for the Human Sensorimotor Cortex

For some experimental approaches in brain imaging, the existing normalization techniques are not always sufficient. This may be the case if the anatomical shape of the region of interest varies substantially across subjects, or if one needs to compare the left and right hemisphere in the same subject. Here we propose a new standard representation, building upon existing normalization methods: Cgrid (Cartesian geometric representation with isometric dimensions). Cgrid is based on imposing a Cartesian grid over a cortical region of interest that is bounded by anatomical (atlas-based) landmarks. We applied this new representation to the sensorimotor cortex and we evaluated its performance by studying the similarity of activation patterns for hand, foot and tongue movements between subjects, and similarity between hemispheres within subjects. The Cgrid similarities were benchmarked against the similarities of activation patterns when transformed into standard MNI space using SPM, and to similarities from FreeSurfer’s surface-based normalization. For both between-subject and between-hemisphere comparisons, similarity scores in Cgrid were high, similar to those from FreeSurfer normalization and higher than similarity scores from SPM’s MNI normalization. This indicates that Cgrid allows for a straightforward way of representing and comparing sensorimotor activity patterns across subjects and between hemispheres of the same subjects.

Similarity analysis of frequent sequential activity pattern mining

Activity pattern classification is extensively studied using multi-person single-day mobile traces. However, human mobility exhibits intra-personal variability and thus single-day activity may not fully capture one’s activity patterns. This paper creates a methodological framework to analyze similarity of activity patterns using frequent sequential pattern mining when multi-person multi-day data is available. Frequent sequential pattern mining discovers the frequently occurring ordered subsequences and is a natural approach of analyzing multi-day travel patterns. Prefix-Span algorithm is implemented to extract frequent patterns for each individual. Then similarity measures are defined to describe the extent to which two travelers’ activity patterns are alike and the regularity of how one repeats her activity patterns from day to day. Based upon the pairwise similarity values between two individuals, hierarchical clustering is conducted to divide travelers into communities. To illustrate these methodologies, 349 travelers’ 19,130 travel activity sequences are extracted from the world’s first connected vehicle testbed in Ann Arbor, Michigan. Three major clusters are identified. Coupled with demographics, these clusters are characterized as “seniors”, “working class”, and “parents”, respectively. Multinomial logistic regression is employed to model to what extent the similarity of socio-demographics can explain that of travel patterns. This work can be extended to either infer an unknown user’s demographics (or customer profiling) based on her activity patterns, or to reconstruct an unknown user’s frequent activity patterns based on her demographics and other similar travelers’ patterns.

Does US expectancy mediate the additive effects of CS-US pairings on contingency instructions? Results from subjective, psychophysiological and neural measures

Verbal instructions are a powerful pathway to learn new fear relations, and an important question has been what fear experience can still add to the effect of such instructions. Therefore, in previous studies, we investigated the effects of pairings between conditioned stimuli (CS) and unconditioned stimuli (US) after CS-US contingency instructions. Although these studies found that CS-US pairings do indeed add to the effects of contingency instructions on subjective, psychophysiological and neural measures of conditioned fear, they also produce increases in US expectancy ratings. In the current report we address whether these enhanced US expectancy ratings can account for the additive effects of CS-US pairings as suggested by expectancy models of fear conditioning. To address this question we made use of pathway models to investigate mediation in within-subjects designs. Our results demonstrate that US expectancy ratings do not mediate the effects of CS-US pairings on fear ratings, the startle reflex or amygdala activation pattern similarity. Additional exploratory analyses, however, revealed that subjective fear ratings do explain the effects of CS-US pairings on the other measures. We discuss how these results relate to expectancy models of fear conditioning and what they implicate for the validity of US expectancy and fear ratings.