Cognitive Neuroimaging Studies Research Articles

Efficient functional localization of language regions in the brain

Important recent advances in the cognitive neuroscience of language have been made using functional localizers to demarcate language-selective regions in individual brains. Although single-subject localizers offer insights that are unavailable in classic group analyses, they require additional scan time that imposes costs on investigators and participants. In particular, the unique practical challenges of scanning children and other special populations has led to less adoption of localizers for neuroimaging research with these theoretically and clinically important groups. Here, we examined how measurements of the spatial extent and functional response profiles of language regions are affected by the duration of an auditory language localizer. We compared how parametrically smaller amounts of data collected from one scanning session affected (i) consistency of group-level whole-brain parcellations, (ii) functional selectivity of subject-level activation in individually defined functional regions of interest (fROIs), (iii) sensitivity and specificity of subject-level whole-brain and fROI activation, and (iv) test-retest reliability of subject-level whole-brain and fROI activation. For many of these metrics, the localizer duration could be reduced by 50-75% while preserving the stability and reliability of both the spatial extent and functional response profiles of language areas. These results indicate that, for most measures relevant to cognitive neuroimaging studies, the brain's language network can be localized just as effectively with 3.5 min of scan time as it can with 12 min. Minimizing the time required to reliably localize the brain's language network allows more effective localizer use in situations where each minute of scan time is particularly precious.

Cognitive Neuroimaging Studies on Poverty and Socioeconomic Status Differences in Children and Families across the World: Translational Insights for Next Decade’s Policy, Health, and Education

This systematic review and meta-analysis of global peer-reviewed neuroimaging findings preliminarily assessed the magnitude of effect sizes (ES) of the influences of family poverty/low socioeconomic status (SES) on children’s neurocognition and whether these were consistently detrimental. The literature search (Web of Science; PUBMED; MEDLINE: PSYCNET; GOOGLE SCHOLAR; SCIENCEDIRECT) included 66 studies from 1988 to 2022; 85% of the studies included were conducted in Western, high-income nations. Bayesian models, corrected by study sizes and variances, revealed ESs were heterogeneous across countries and measurements. Bayesian and standard hypothesis testing indicated high and low SES groups showed similar behavioral performances in neuroimaging-concurrent tasks. Except for Magnetic Resonance Imaging studies, ESs were small-to-intermediate with modest reliability. The strongest ESs were found for attention, mathematical performance, language, and cortical volume, followed by intermediate ESs for reading and socioemotional processes. Differentials in resting activity and connectivity, working memory, and executive functions yielded small effects. A bibliometric analysis showed a significant proportion of the literature attributed neurocognitive deficits to low SES, despite overlooking the under-representativity of non-Western and low-income countries, potential influences of racial/ethnic differences, and measurement sensitivity/specificity discrepancies. To reach United Nations Sustainable Development Goals, policies and interventions should consider regional, structural, or environmental ecologies beyond the individual, critically probing implicit deficit attributions.

Decreased interhemispheric connectivity and increased cortical excitability in unmedicated schizophrenia: A prefrontal interleaved TMS fMRI study

BackgroundPrefrontal abnormalities in schizophrenia have consistently emerged from resting state and cognitive neuroimaging studies. However, these correlative findings require causal verification via combined imaging/stimulation approaches. To date, no interleaved transcranial magnetic stimulation and functional magnetic resonance imaging study (TMS fMRI) has probed putative prefrontal cortex abnormalities in schizophrenia. Objective/Hypothesis: We hypothesized that subjects with schizophrenia would show significant hyperexcitability at the site of stimulation (BA9) and decreased interhemispheric functional connectivity. MethodsWe enrolled 19 unmedicated subjects with schizophrenia and 22 controls. All subjects underwent brain imaging using a 3T MRI scanner with a SENSE coil. They also underwent a single TMS fMRI session involving motor threshold (rMT) determination, structural imaging, and a parametric TMS fMRI protocol with 10 Hz triplet pulses at 0, 80, 100 and 120% rMT. Scanning involved a surface MR coil optimized for bilateral prefrontal cortex image acquisition. ResultsOf the original 41 enrolled subjects, 8 subjects with schizophrenia and 11 controls met full criteria for final data analyses. At equal TMS intensity, subjects with schizophrenia showed hyperexcitability in left BA9 (p = 0.0157; max z-score = 4.7) and neighboring BA46 (p = 0.019; max z-score = 4.47). Controls showed more contralateral functional connectivity between left BA9 and right BA9 through increased activation in right BA9 (p = 0.02; max z-score = 3.4). GM density in subjects with schizophrenia positively correlated with normalized prefrontal to motor cortex ratio of the corresponding distance from skull to cortex ratio (S-BA9/S-MC) (r = 0.83, p = 0.004). ConclusionsSubjects with schizophrenia showed hyperexcitability in left BA9 and impaired interhemispheric functional connectivity compared to controls. Interleaved TMS fMRI is a promising tool to investigate prefrontal dysfunction in schizophrenia.

Real-time Adaptive Design Optimization Within Functional MRI Experiments

Efficient data collection is an important goal in cognitive neuroimaging studies because of the high cost of data acquisition. One method of improving efficiency is to maximize the informativeness of the data collected on each trial. We propose an Adaptive Design Optimization (Cavagnaro et al. Neural Computation 22, 887–905 2010; Myung et al. Journal of Mathematical Psychology 57, 53–67 2013) procedure to optimize the sequencing of stimuli for model-based functional neuroimaging studies. Our method uses the Joint Modeling Framework (Turner et al. NeuroImage 72, 193–206 2013, 2019) to maximize the information learned about how the brain produces a behavior by integrating over neural and behavioral data simultaneously. We validate our method in simulation and real-world experiments by showing how Adaptive Design Optimization proposes the optimal stimulus sequence to reduce uncertainty and improve accuracy from a Bayesian perspective.

Eye Movement-Related Confounds in Neural Decoding of Visual Working Memory Representations.

A relatively new analysis technique, known as neural decoding or multivariate pattern analysis (MVPA), has become increasingly popular for cognitive neuroimaging studies over recent years. These techniques promise to uncover the representational contents of neural signals, as well as the underlying code and the dynamic profile thereof. A field in which these techniques have led to novel insights in particular is that of visual working memory (VWM). In the present study, we subjected human volunteers to a combined VWM/imagery task while recording their neural signals using magnetoencephalography (MEG). We applied multivariate decoding analyses to uncover the temporal profile underlying the neural representations of the memorized item. Analysis of gaze position however revealed that our results were contaminated by systematic eye movements, suggesting that the MEG decoding results from our originally planned analyses were confounded. In addition to the eye movement analyses, we also present the original analyses to highlight how these might have readily led to invalid conclusions. Finally, we demonstrate a potential remedy, whereby we train the decoders on a functional localizer that was specifically designed to target bottom-up sensory signals and as such avoids eye movements. We conclude by arguing for more awareness of the potentially pervasive and ubiquitous effects of eye movement-related confounds.

The impact of physiological noise correction on fMRI at 7 T

Cognitive neuroimaging studies typically require fast whole brain image acquisition with maximal sensitivity to small BOLD signal changes. To increase the sensitivity, higher field strengths are often employed, since they provide an increased image signal-to-noise ratio (SNR). However, as image SNR increases, the relative contribution of physiological noise to the total time series noise will be greater compared to that from thermal noise. At 7 T, we studied how the physiological noise contribution can be best reduced for EPI time series acquired at three different spatial resolutions (1.1 mm × 1.1 mm × 1.8 mm, 2 mm × 2 mm × 2 mm and 3 mm × 3 mm × 3 mm). Applying optimal physiological noise correction methods improved temporal SNR (tSNR) and increased the numbers of significantly activated voxels in fMRI visual activation studies for all sets of acquisition parameters. The most dramatic results were achieved for the lowest spatial resolution, an acquisition parameter combination commonly used in cognitive neuroimaging which requires high functional sensitivity and temporal resolution (i.e. 3 mm isotropic resolution and whole brain image repetition time of 2 s). For this data, physiological noise models based on cardio-respiratory information improved tSNR by approximately 25% in the visual cortex and 35% sub-cortically. When the time series were additionally corrected for the residual effects of head motion after retrospective realignment, the tSNR was increased by around 58% in the visual cortex and 71% sub-cortically, exceeding tSNR ~ 140. In conclusion, optimal physiological noise correction at 7 T increases tSNR significantly, resulting in the highest tSNR per unit time published so far. This tSNR improvement translates into a significant increase in BOLD sensitivity, facilitating the study of even subtle BOLD responses.

Source monitoring 15 years later: What have we learned from fMRI about the neural mechanisms of source memory?

Focusing primarily on functional magnetic resonance imaging (fMRI), this article reviews evidence regarding the roles of subregions of the medial temporal lobes, prefrontal cortex, posterior representational areas, and parietal cortex in source memory. In addition to evidence from standard episodic memory tasks assessing accuracy for neutral information, the article considers studies assessing the qualitative characteristics of memories, the encoding and remembering of emotional information, and false memories, as well as evidence from populations that show disrupted source memory (older adults, individuals with depression, posttraumatic stress disorder, or schizophrenia). Although there is still substantial work to be done, fMRI is advancing understanding of source memory and highlighting unresolved issues. A continued 2-way interaction between cognitive theory, as illustrated by the source monitoring framework (M. K. Johnson, S. Hashtroudi, & D. S. Lindsay, 1993), and evidence from cognitive neuroimaging studies should clarify conceptualization of cognitive processes (e.g., feature binding, retrieval, monitoring), prior knowledge (e.g., semantics, schemas), and specific features (e.g., perceptual and emotional information) and of how they combine to create true and false memories.

Attention to Arrows: Pointing to a New Direction

It was long believed that central arrows needed to be spatially predictive to produce a shift in spatial attention. Recent evidence indicates, however, that central spatially nonpredictive directional cues, like arrows, will trigger reflexive shifts in attention. We asked what this recent discovery means for past studies that used predictive directional cues such as arrows. Our findings indicate that predictive arrows produce attention effects that greatly exceed the individual or summed effects of reflexive orienting to nonpredictive arrows and volitional orienting to predictive numbers. This suggests that the especially large effect produced by predictive arrows reflects an interaction between reflexive and volitional orienting. Given the broad application of the predictive arrow cueing paradigm in both past and current research, the present data shed new light on a wide range of investigations, from psychophysical studies of basic attention to behavioural and neuroimaging studies of cognition and social development.

Cognitive neuroimaging: Cognitive science out of the armchair

Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some ultra-cognitive scientists assert that these experiments can never be of relevance to the study of cognition. Their reasoning reflects an adherence to a functionalist philosophy that arbitrarily and purposefully distinguishes mental information-processing systems from brain or brain-like operations. This article addresses whether data from properly conducted functional neuroimaging studies can inform and subsequently constrain the assumptions of theoretical cognitive models. The article commences with a focus upon the functionalist philosophy espoused by the ultra-cognitive scientists, contrasting it with the materialist philosophy that motivates both cognitive neuroimaging investigations and connectionist modelling of cognitive systems. Connectionism and cognitive neuroimaging share many features, including an emphasis on unified cognitive and neural models of systems that combine localist and distributed representations. The utility of designing cognitive neuroimaging studies to test (primarily) connectionist models of cognitive phenomena is illustrated using data from functional magnetic resonance imaging (fMRI) investigations of language production and episodic memory.

Variance maps as a novel tool for localizing regions of interest in imaging studies of individual differences

Cognitive neuroimaging studies of individual differences seek to reveal brain mechanisms of cognition by associating intersubject variability in brain activation with other variables of interest, such as sex, personality trait, or mood state. The choice of a priori regions of interest (ROIs) raises problems, because the selection criterion is typically consistent activation across prior studies, suggesting little intersubject variability. Here, we introduce a novel approach for selecting regions that are defined on the basis of their variance characteristics, rather than on the basis of their location or because of theoretical expectations. These regions of variance (ROVs) constitute the search space with which to assess how much of the observed variance can be ascribed to specific variables of interest. We compare the ROI and ROV approaches by applying each to the same data set and suggest that the conjunction of both methods may yield the greatest likelihood of capturing the rich relation between brain and behavior, while limiting the search space for statistical analyses and minimizing false positive errors.

Human cortical responses during one-bit delayed-response tasks: An fMRI study

Neuroimaging study of cognition across aging requires simple tasks ensuring: (i) high rate of correct performances in neurophysiological settings; and (ii) significant modulation of cortical activity. As a preliminary step, the present functional magnetic resonance imaging (fMRI) study tested the hypothesis that very simple delayed-response tasks fit these requirements in normal young adults. The short-term memory (STM) variant included a sequence of cue stimulus (two vertical bars), delay period (blank screen for only 5 s), go stimulus, and motor response compatible with the taller vertical bar. Noteworthy, the retention (only one bit) could be based on visuo-spatial, phonological, and somatomotor coding. In the control variant (no STM, NSTM), the cue stimulus was present during the delay period. Results showed high rate of correct performances in both tasks (about 95%). Compared to the NSTM task (delay period), the STM task enhanced cortical responses in bilateral dorsolateral prefrontal (Brodmann area 8–9 (BA 8–9)), lateral premotor (BA 6L), medial premotor (BA 6M), inferior parietal (BA 40), and superior parietal (BA 7) areas. In the STM task, cortical responses were stronger in right than left BA 8–9 and BA 6L. These results indicate that, in normal young adults, a simple STM variant of delayed-response tasks (one bit to be retained) is correctly performed and enhances bilateral fronto-parietal responses. Therefore, it may be used for future cognitive neuroimaging studies on aging.

Can literacy change brain anatomy?

Several studies have postulated that education and/or literacy may not only protect against the effects of biological ageing (Albert et al., 1995; Christensen & Henderson, 1991; Orrell & Sahakian, 1995), but also against the clinical manifestation of cerebral neuropathology (Katzman, 1993; Stern, 2002; Stern, Gurland, Tatemichi, Tang, Wilder, & Mayeux, 1994; Zhang et al., 1990). In clinical neuropsychology, much debate has centred on whether the brain is more likely to degenerate as a result of overuse or underuse; while some epidemiological studies have suggested that active engagement in intellectual, social, and physical activities may delay the cognitive deterioration associated with normal ageing (Scarmeas, Levy, Tang, Manly, & Stern, 2001), other studies have emphasized that the protective effect of education is not always observed but depends upon the specific cognitive ability that is measured (Ardila, Ostrosky-Solis, Rosselli, & Gomez, 2000; Ostrosky-Solis, Ardila, Rosselli, Lopez, & Mendoza, 1998). Ostrosky-Solis (2002) points out that protection or age-related decline attenuation in well-educated subjects is highly related to verbal abilities; thus, education and verbal advantage could serve as a means of compensatory strategies, such as using verbal cues to aid recall or encoding visuospatial tasks with language. These are the strategies provided by formal education. The use of these strategies could mask otherwise similar rates of biological ageing among different educational groups, and this advantage, coupled with the effects of several important variables such as good health, appropriate occupation, and active engagement with the surrounding environment, could explain why cognitive stimulation can provide some moderating influence on the complex changes in cognitive performance associated with ageing. It has also been reported that Alzheimer’s disease not only has a later onset but that it is less severe in highly educated people (Katzman, 1993; Stern et al., 1994). This association of high education with late age of onset of dementia has been considered as an evidence of cognitive and/or brain reserve (Katzman, 1993; Mortimer, 1988; Satz, 1993; Stern, 2002). The articles presented in this Special Issue analyse the impact of literacy on the anatomic and functional organization of the adult brain. Cognitive neuroimaging studies, event-related potentials, neuropsychological data of literate and illiterate subjects, and discussion regarding the origins and evolution of reading and writing are presented. Stern, Scarmeas, and Habeck point out that the cognitive reserve model suggests that variables such as education and IQ are associated with cognitive reserve (CR) and may mediate differential susceptibility to age-related memory changes. They propose two complementary facets to CR: reserve—individual differences in the capacity to perform task—and compensation—the use of alternate brain networks or cognitive processes to cope with brain pathology. However, up to now the neurophysiologic substrate of CR has not been established. Therefore in order to explore the anatomical basis for CR in healthy young and old individuals, they used H215O PET to analyse the relationship between CR and task-related activation during the performance of a nonverbal recognition memory test. The first two studies focused on young subjects, and found either brain areas or brain networks where the amount of increased activation correlated with CR. The third study compared activation patterns of young and elderly individuals and found locations where the relation between activation and CR differed

In vivo mapping of functional domains and axonal connectivity in cat visual cortex using magnetic resonance imaging.

Noninvasive cognitive neuroimaging studies based on functional magnetic resonance imaging (fMRI) are of ever-increasing importance for basic and clinical neurosciences. The explanatory power of fMRI could be greatly expanded, however, if the pattern of the neuronal circuitry underlying functional activation could be made visible in an equally noninvasive manner. In this study, blood oxygenation level-dependent (BOLD)-based fMRI and diffusion tensor imaging (DTI) were performed in the same cat visual cortex, and the foci of fMRI activation utilized as seeding points for 3D DTI fiber reconstruction algorithms, thus providing the map of the axonal circuitry underlying visual information processing. The methods developed in this study will lay the foundation for in vivo neuroanatomy and the ability for noninvasive longitudinal studies of brain development.

Neural bases of image and language interactions

Mental visual imagery and language are the two main types of representation used by humans. These two modes of mental representations are not exclusive from each other. In fact, the importance of mental imagery in human cognition comes in part from the interactions between mental image and language. Several cognitive neuroimaging studies have attempted to unravel the neural bases of these interactions. A consistent result from these studies is that mental images generated from verbal description elicit activations in both visual and language cortices. Visual cortex regions include occipital areas of the so‐called dorsal and ventral routes, whereas language areas concern both the temporal and frontal cortices, e.g., both the comprehension and production poles of language. Interestingly, it was also found that language areas are more likely to address a representation when language is the only source of information than when imagery and language are used in conjunction, which demonstrates a modulation of the activity in these areas by the mental imagery task. Overall, these findings provide a neural substrate to the dual coding theory developed by Paivio. Moreover, the fact that the same associative visual regions are activated during mental imagery triggered by either verbal description or visual encoding provides a neural base to the observation that these two types of images share common structural properties. Meanwhile, the involvement of primary visual area (PVA) during mental imagery activity remains a debated issue. First, recent results have demonstrated that PVA is not involved in some kinds of mental imagery, especially during spatial mental imagery. Second, studies have also indicated that the encoding modality, either visual or verbal, may have an impact on the neural substrates of mental images.

Restriction of task processing time affects cortical activity during processing of a cognitive task: an event-related slow cortical potential study

As is known from psychometrics, restriction of task processing time by the instruction to respond as quickly and accurately as possible leads to task-unspecific cognitive processing. Since this task processing mode is used in most functional neuroimaging studies of human cognition, this may evoke cortical activity that is functionally not essential for the particular task under investigation. Using topographic recordings of event-related slow cortical potentials, two experiments have been performed to investigate whether cortical activity during processing of a visuo-spatial imagery task is substantially influenced by the time provided to process the task. Furthermore, it was investigated whether this effect is additionally modulated by a subject’s task-specific ability. The instruction to respond as quickly and accurately as possible led to increased negative slow cortical potential amplitudes over parietal and frontal regions and significantly interacted with task-specific ability. While cortical activity recorded over parietal and frontal regions was different between subjects with low and high spatial ability when processing time was unrestricted, no such differences were found between ability groups when subjects were instructed to answer both quickly and accurately. These results suggest that restricting processing time has considerable effects on the amount and the pattern of brain activity during cognitive processing and should be taken into account more explicitly in the experimental design and interpretation of neuroimaging studies of cognition.

Mapping Neural Interactivity onto Regional Activity: An Analysis of Semantic Processing and Response Mode Interactions

Neuroimaging studies of cognition have typically been designed to identify brain regions that are active during a cognitive process. However, identifying how brain regionsinteractmay be equally important. In a recent study we found that the pattern of activation associated with a semantic taskdiffereddepending on how subjects made a response, suggesting that there was an interaction between the neural systems underlying response mode and semantic processing (J. M. Jenningset al.,1997,NeuroImage5,229–239). This result raises two important questions, which we examined here: (1) How did the regions underlying semantic performance influence one another, or interact, to produce a different pattern of activation in each case? (2) What can be learned about the neurobiology of semantic processing when different regions are identified as a function of response? We addressed these questions using structural equation modeling. This technique produced functional network models representing the effect of different regions on each other during the semantic task for each response. A common network of regions associated with semantic processing was observed and included the left inferior frontal and left superior temporal cortices, with other regions brought into that network depending on response (e.g., right middle frontal). Moreover, changes in the influences among these regions across response condition predicted the pattern of activation found previously. These results show how an arbitrary response can affect the neural pathways associated with a cognitive process, likely due to the parallel and reentrant organization of the brain, and emphasize the importance of examining functional connections when studying cognition.