Publishing your code can help you find your own errors

Publishing your code forces you to "clean it up", which can help identify errors.

As you can guess from the post title, in the process of cleaning up the code and files for uploading to the OSF, I found a coding bug. (There can't be many more horrible feelings as a scientist than finding a bug in the code for a paper that's already been accepted!) The bug was that when calculating the accuracy across the cross-validation folds, one of the fold's accuracies was omitted. Thankfully, this was a 15-fold cross-validation, so fixing the code so that the mean is calculated over all 15 folds instead of just 14 made only a minuscule difference in the final results, nothing that changed any interpretations.

Attentional selection predicted by reinforcement learning of task-relevant stimulus features weighted by value-independent stickiness

Attention includes processes that evaluate stimuli relevance, select the most relevant stimulus against less relevant stimuli, and bias choice behavior toward the selected information. It is not clear how these processes interact. Here, we captured these processes in a reinforcement learning framework applied to a feature-based attention task that required macaques to learn and update the value of stimulus features while ignoring nonrelevant sensory features, locations, and action plans. We found that value-based reinforcement learning mechanisms could account for feature-based attentional selection and choice behavior but required a value-independent stickiness selection process to explain selection errors while at asymptotic behavior. By comparing different reinforcement learning schemes, we found that trial-by-trial selections were best predicted by a model that only represents expected values for the task-relevant feature dimension, with nonrelevant stimulus features and action plans having only a marginal influence on covert selections. These findings show that attentional control subprocesses can be described by (1) the reinforcement learning of feature values within a restricted feature space that excludes irrelevant feature dimensions, (2) a stochastic selection process on feature-specific value representations, and (3) value-independent stickiness toward previous feature selections akin to perseveration in the motor domain. We speculate that these three mechanisms are implemented by distinct but interacting brain circuits and that the proposed formal account of feature-based stimulus selection will be important to understand how attentional subprocesses are implemented in primate brain networks.

 

Phonological processing in primary progressive aphasia

Individuals with primary progressive aphasia (PPA) show selective breakdown in regions within the proposed dorsal (articulatory–phonological) and ventral (lexical–semantic) pathways involved in language processing. Phonological STM impairment, which has been attributed to selective damage to dorsal pathway structures, is considered to be a distinctive feature of the logopenic variant of PPA. By contrast, phonological abilities are considered to be relatively spared in the semantic variant and are largely unexplored in the nonfluent/agrammatic variant. Comprehensive assessment of phonological ability in the three variants of PPA has not been undertaken. We investigated phonological processing skills in a group of participants with PPA as well as healthy controls, with the goal of identifying whether patterns of performance support the dorsal versus ventral functional–anatomical framework and to discern whether phonological ability differs among PPA subtypes. We also explored the neural bases of phonological performance using voxel-based morphometry. Phonological performance was impaired in patients with damage to dorsal pathway structures (nonfluent/agrammatic and logopenic variants), with logopenic participants demonstrating particular difficulty on tasks involving nonwords. Binary logistic regression revealed that select phonological tasks predicted diagnostic group membership in the less fluent variants of PPA with a high degree of accuracy, particularly in conjunction with a motor speech measure. Brain–behavior correlations indicated a significant association between the integrity of gray matter in frontal and temporoparietal regions of the left hemisphere and phonological skill. Findings confirm the critical role of dorsal stream structures in phonological processing and demonstrate unique patterns of impaired phonological processing in logopenic and nonfluent/agrammatic variants of PPA.

A network approach to mixing delegates at meetings

I don't like the "speed dating" term but otherwise it's an interesting approach.

Over the two days of the conference, we dedicated two 90 minute sessions to speed dating. The first session consisted of five rounds of ice breakers in which each delegate was paired with another delegate with whom they had little in common (based on the methods they knew about and the people they had collaborated with). The intention was to cause the delegates to meet new and different people. Each round lasted 15 minutes, giving enough time for scientists to discuss their own work while still keeping the meetings brief and to the point. The atmosphere of the meetings was highly informal–coffee and refreshments were provided, and scientists had the choice to sit down at small tables or simply walk around near posters and discuss each other’s results.

Eve Marder on owning your mistakes

In another example, one of my PhD students recently failed to replicate some of our previously published observations, for reasons we still don't fully understand. This was obviously painful, but we published the most complete description of the new data and our best assessment of what could be responsible for the discrepancy (including the possibility that our wild-caught crab populations are affected by climate change). Ironically, the first version of the manuscript was rejected (not by eLife) because a reviewer said we shouldn't be allowed to publish something that disagreed with our own prior observations!

Effect of trial-to-trial variability on optimal event-related fMRI design: Implications for Beta-series correlation and multi-voxel pattern analysis

Functional magnetic resonance imaging (fMRI) studies typically employ rapid, event-related designs for behavioral reasons and for reasons associated with statistical efficiency. Efficiency is calculated from the precision of the parameters (Betas) estimated from a General Linear Model (GLM) in which trial onsets are convolved with a Hemodynamic Response Function (HRF). However, previous calculations of efficiency have ignored likely variability in the neural response from trial to trial, for example due to attentional fluctuations, or different stimuli across trials. Here we compare three GLMs in their efficiency for estimating average and individual Betas across trials as a function of trial variability, scan noise and Stimulus Onset Asynchrony (SOA): “Least Squares All” (LSA), “Least Squares Separate” (LSS) and “Least Squares Unitary” (LSU). Estimation of responses to individual trials in particular is important for both functional connectivity using “Beta-series correlation” and “multi-voxel pattern analysis” (MVPA). Our simulations show that the ratio of trial-to-trial variability to scan noise impacts both the optimal SOA and optimal GLM, especially for short SOAs < 5 s: LSA is better when this ratio is high, whereas LSS and LSU are better when the ratio is low. For MVPA, the consistency across voxels of trial variability and of scan noise is also critical. These findings not only have important implications for design of experiments using Beta-series regression and MVPA, but also statistical parametric mapping studies that seek only efficient estimation of the mean response across trials.

Comparison of cortical folding measures for evaluation of developing human brain

We evaluated 22 measures of cortical folding, 20 derived from local curvature (curvature-based measures) and two based on other features (sulcal depth and gyrification index), for their capacity to distinguish between normal and aberrant cortical development. Cortical surfaces were reconstructed from 12 term-born control and 63 prematurely-born infants. Preterm infants underwent 2–4 MR imaging sessions between 27 and 42 weeks postmenstrual age (PMA). Term infants underwent a single MR imaging session during the first postnatal week. Preterm infants were divided into two groups. One group (38 infants) had no/minimal abnormalities on qualitative assessment of conventional MR images. The second group (25 infants) consisted of infants with injury on conventional MRI at term equivalent PMA. For both preterm infant groups, all folding measures increased or decreased monotonically with increasing PMA, but only sulcal depth and gyrification index differentiated preterm infants with brain injury from those without. We also compared scans obtained at term equivalent PMA (36–42 weeks) for all three groups. No curvature-based measured distinguished between the groups, whereas sulcal depth distinguished term control from injured preterm infants and gyrification index distinguished all three groups. When incorporating total cerebral volume into the statistical model, sulcal depth no longer distinguished between the groups, though gyrification index distinguished between all three groups and positive shape index distinguished between the term control and uninjured preterm groups. We also analyzed folding measures averaged over brain lobes separately. These results demonstrated similar patterns to those obtained from the whole brain analyses. Overall, though the curvature-based measures changed during this period of rapid cerebral development, they were not sensitive for detecting the differences in folding associated with brain injury and/or preterm birth. In contrast, gyrification index was effective in differentiating these groups.

A subject-specific framework for in vivo myeloarchitectonic analysis using high resolution quantitative MRI

Structural magnetic resonance imaging can now resolve laminar features within the cerebral cortex in vivo. A variety of intracortical contrasts have been used to study the cortical myeloarchitecture with the purpose of mapping cortical areas in individual subjects. In this article, we first briefly review recent advances in MRI analysis of cortical microstructure to portray the potential and limitations of the current state-of-the-art. We then present an integrated framework for the analysis of intracortical structure, composed of novel image processing tools designed for high resolution cortical images. The main features of our framework are the segmentation of quantitative T1 maps to delineate the cortical boundaries (Bazin et al., 2014), and the use of an equivolume layering model to define an intracortical coordinate system that follows the anatomical layers of the cortex (Waehnert et al., 2014). We evaluate the framework with 150 μm isotropic post mortem T2∗-weighted images and 0.5 mm isotropic in vivo T1 maps, a quantitative index of myelin content. We study the laminar structure of the primary visual cortex (Brodmann area 17) in the post mortem and in vivo data, as well as the central sulcus region in vivo, in particular Brodmann areas 1, 3b and 4. We also investigate the impact of the layering models on the relationship between T1 and cortical curvature. Our experiments demonstrate that the equivolume intracortical surfaces and transcortical profiles best reflect the laminar structure of the cortex in areas of curvature in comparison to the state-of-the-art equidistant and Laplace implementations. This framework generates a subject specific intracortical coordinate system, the basis for subsequent architectonic analyses of the cortex. Any structural or functional contrast co-registered to the T1 maps, used to segment the cortex, can be sampled on the curved grid for analysis. This work represents an important step towards in vivo structural brain mapping of individual subjects.

Aging of cerebral white matter in middle-aged and older adults: A seven-year follow-up

The few extant reports of longitudinal white matter (WM) changes in healthy aging, using diffusion tensor imaging (DTI), reveal substantial differences in change across brain regions and DTI indices. According to the “last-in-first-out” hypothesis of brain aging late-developing WM tracts may be particularly vulnerable to advanced age. To test this hypothesis we compared age-related changes in association, commissural and projection WM fiber regions using a skeletonized, region of interest DTI approach. Using linear mixed effect models, we evaluated the influences of age and vascular risk at baseline on seven-year changes in three indices of WM integrity and organization (axial diffusivity, AD, radial diffusivity, RD, and fractional anisotropy, FA) in healthy middle-aged and older adults (mean age = 65.4, SD = 9.0 years). Association fibers showed the most pronounced declines over time. Advanced age was associated with greater longitudinal changes in RD and FA, independent of fiber type. Furthermore, older age was associated with longitudinal RD increases in late-developing, but not early-developing projection fibers. These findings demonstrate the increased vulnerability of later developing WM regions and support the “last-in-first-out” hypothesis of brain aging.

Longitudinal assessment of white matter abnormalities following sports-related concussion

There is great interest in developing physiological-based biomarkers such as diffusion tensor imaging to aid in the management of concussion, which is currently entirely dependent on clinical judgment. However, the time course for recovery of white matter abnormalities following sports-related concussion (SRC) is unknown. We collected diffusion tensor imaging and behavioral data in forty concussed collegiate athletes on average 1.64 days (T1; n = 33), 8.33 days (T2; n = 30), and 32.15 days post-concussion (T3; n = 26), with healthy collegiate contact-sport athletes (HA) serving as controls (n = 46). We hypothesized that fractional anisotropy (FA) would be increased acutely and partially recovered by one month post-concussion. Mood symptoms were assessed using structured interviews. FA differences were assessed using both traditional and subject-specific analyses. An exploratory analysis of tau plasma levels was conducted in a subset of participants. Results indicated that mood symptoms improved over time post-concussion, but remained elevated at T3 relative to HA. Across both group and subject-specific analyses, concussed athletes exhibited increased FA in several white matter tracts at each visit post-concussion with no longitudinal evidence of recovery. Increased FA at T1 and T3 was significantly associated with an independent, real-world outcome measure for return-to-play. Finally, we observed a nonsignificant trend for reduced tau in plasma of concussed athletes at T1 relative to HA, with tau significantly increasing by T2. These results suggest white matter abnormalities following SRC may persist beyond one month and have potential as an objective biomarker for concussion outcome

Functional segregation of human dorsomedial prefrontal cortex

The human dorsomedial prefrontal cortex (dmPFC) has been implicated in various complex cognitive processes, including social cognition. To unravel its functional organization, we assessed the dmPFC's regional heterogeneity, connectivity patterns, and functional profiles. First, the heterogeneity of a dmPFC seed, engaged during social processing, was investigated by assessing local differences in whole-brain coactivation profiles. Second, functional connectivity of the ensuing dmPFC clusters was compared by task-constrained meta-analytic coactivation mapping and task-unconstrained resting-state correlations. Third, dmPFC clusters were functionally profiled by forward/reverse inference. The dmPFC seed was thus segregated into 4 clusters (rostroventral, rostrodorsal, caudal-right, and caudal-left). Both rostral clusters were connected to the amygdala and hippocampus and associated with memory and social cognitive tasks in functional decoding. The rostroventral cluster exhibited strongest connectivity to the default mode network. Unlike the rostral segregation, the caudal dmPFC was divided by hemispheres. The caudal-right cluster was strongly connected to a frontoparietal network (dorsal attention network), whereas the caudal-left cluster was strongly connected to the anterior midcingulate cortex and bilateral anterior insula (salience network). In conclusion, we demonstrate that a dmPFC seed reflecting social processing can be divided into 4 separate functional modules that contribute to distinct facets of advanced human cognition.

Slow-theta-to-gamma phase–amplitude coupling in human hippocampus supports the formation of new episodic memories

Phase–amplitude coupling (PAC) has been proposed as a neural mechanism for coordinating information processing across brain regions. Here we sought to characterize PAC in the human hippocampus, and in temporal and frontal cortices, during the formation of new episodic memories. Intracranial recordings taken as 56 neurosurgical patients studied and recalled lists of words revealed significant hippocampal PAC, with slow-theta activity (2.5–5 Hz) modulating gamma band activity (34–130 Hz). Furthermore, a significant number of hippocampal electrodes exhibited greater PAC during successful than unsuccessful encoding, with the gamma activity at these sites coupled to the trough of the slow-theta oscillation. These same conditions facilitate LTP in animal models, providing a possible mechanism of action for this effect in human memory. Uniquely in the hippocampus, phase preference during item encoding exhibited a biphasic pattern. Overall, our findings help translate between the patterns identified during basic memory tasks in animals and those present during complex human memory encoding. We discuss the unique properties of human hippocampal PAC and how our findings relate to influential theories of information processing based on theta–gamma interactions.

Maturation of sensori-motor functional responses in the preterm brain

Preterm birth engenders an increased risk of conditions like cerebral palsy and therefore this time may be crucial for the brain's developing sensori-motor system. However, little is known about how cortical sensori-motor function matures at this time, whether development is influenced by experience, and about its role in spontaneous motor behavior. We aimed to systematically characterize spatial and temporal maturation of sensori-motor functional brain activity across this period using functional MRI and a custom-made robotic stimulation device. We studied 57 infants aged from 30 + 2 to 43 + 2 weeks postmenstrual age. Following both induced and spontaneous right wrist movements, we saw consistent positive blood oxygen level–dependent functional responses in the contralateral (left) primary somatosensory and motor cortices. In addition, we saw a maturational trend toward faster, higher amplitude, and more spatially dispersed functional responses; and increasing integration of the ipsilateral hemisphere and sensori-motor associative areas. We also found that interhemispheric functional connectivity was significantly related to ex-utero exposure, suggesting the influence of experience-dependent mechanisms. At term equivalent age, we saw a decrease in both response amplitude and interhemispheric functional connectivity, and an increase in spatial specificity, culminating in the establishment of a sensori-motor functional response similar to that seen in adults.

Resting-state network complexity and magnitude are reduced in prematurely born infants

Premature birth is associated with high rates of motor and cognitive disability. Investigations have described resting-state functional magnetic resonance imaging (rs-fMRI) correlates of prematurity in older children, but comparable data in the neonatal period remain scarce. We studied 25 term-born control infants within the first week of life and 25 very preterm infants (born at gestational ages ranging from 23 to 29 weeks) without evident structural injury at term equivalent postmenstrual age. Conventional resting-state network (RSN) mapping revealed only modest differences between the term and prematurely born infants, in accordance with previous work. However, clear group differences were observed in quantitative analyses based on correlation and covariance matrices representing the functional MRI time series extracted from 31 regions of interest in 7 RSNs. In addition, the maximum likelihood dimensionality estimates of the group-averaged covariance matrices in the term and preterm infants were 5 and 3, respectively, indicating that prematurity leads to a reduction in the complexity of rs-fMRI covariance structure. These findings highlight the importance of quantitative analyses of rs-fMRI data and suggest a more sensitive method for delineating the effects of preterm birth in infants without evident structural injury.

Generation and evaluation of a cortical area parcellation from resting-state correlations

The cortical surface is organized into a large number of cortical areas; however, these areas have not been comprehensively mapped in the human. Abrupt transitions in resting-state functional connectivity (RSFC) patterns can noninvasively identify locations of putative borders between cortical areas (RSFC-boundary mapping; Cohen et al. 2008). Here we describe a technique for using RSFC-boundary maps to define parcels that represent putative cortical areas. These parcels had highly homogenous RSFC patterns, indicating that they contained one unique RSFC signal; furthermore, the parcels were much more homogenous than a null model matched for parcel size when tested in two separate datasets. Several alternative parcellation schemes were tested this way, and no other parcellation was as homogenous as or had as large a difference compared with its null model. The boundary map-derived parcellation contained parcels that overlapped with architectonic mapping of areas 17, 2, 3, and 4. These parcels had a network structure similar to the known network structure of the brain, and their connectivity patterns were reliable across individual subjects. These observations suggest that RSFC-boundary map-derived parcels provide information about the location and extent of human cortical areas. A parcellation generated using this method is available at .

Organizing principles of human cortical development—Thickness and area from 4 to 30 years

The human cerebral cortex undergoes a protracted, regionally heterogeneous development well into young adulthood. Cortical areas that expand the most during human development correspond to those that differ most markedly when the brains of macaque monkeys and humans are compared. However, it remains unclear to what extent this relationship derives from allometric scaling laws that apply to primate brains in general, or represents unique evolutionary adaptations. Furthermore, it is unknown whether the relationship only applies to surface area (SA), or also holds for cortical thickness (CT). In 331 participants aged 4 to 30, we calculated age functions of SA and CT, and examined the correspondence of human cortical development with macaque to human expansion, and with expansion across nonhuman primates. CT followed a linear negative age function from 4 to 30 years, while SA showed positive age functions until 12 years with little further development. Differential cortical expansion across primates was related to regional maturation of SA and CT, with age trajectories differing between high- and low-expanding cortical regions. This relationship adhered to allometric scaling laws rather than representing uniquely macaque–human differences: regional correspondence with human development was as large for expansion across nonhuman primates as between humans and macaque.