Publications

Abstract

Spinocerebellar ataxia type 14 (SCA14) is a subtype of the autosomal dominant cerebellar ataxias that is characterized by slowly progressive cerebellar dysfunction and neurodegeneration. SCA14 is caused by mutations in the PRKCG gene, encoding protein kinase C gamma (PKCγ). Despite the identification of 40 distinct disease-causing mutations in PRKCG, the pathological mechanisms underlying SCA14 remain poorly understood. Here we report the molecular neuropathology of SCA14 in post-mortem cerebellum and in human patient-derived induced pluripotent stem cells (iPSCs) carrying two distinct SCA14 mutations in the C1 domain of PKCγ, H36R and H101Q. We show that endogenous expression of these mutations results in the cytoplasmic mislocalization and aggregation of PKCγ in both patient iPSCs and cerebellum. PKCγ aggregates were not efficiently targeted for degradation. Moreover, mutant PKCγ was found to be hyper-activated, resulting in increased substrate phosphorylation. Together, our findings demonstrate that a combination of both, loss-of-function and gain-of-function mechanisms are likely to underlie the pathogenesis of SCA14, caused by mutations in the C1 domain of PKCγ. Importantly, SCA14 patient iPSCs were found to accurately recapitulate pathological features observed in post-mortem SCA14 cerebellum, underscoring their potential as relevant disease models and their promise as future drug discovery tools.

Abstract

Electroencephalography (EEG) provides high temporal resolution cognitive information from non-invasive recordings. However, one of the common practices-using a subset of sensors in ERP analysis is hard to provide a holistic and precise dynamic results. Selecting or grouping subsets of sensors may also be subject to selection bias, multiple comparison, and further complicated by individual differences in the group-level analysis. More importantly, changes in neural generators and variations in response magnitude from the same neural sources are difficult to separate, which limit the capacity of testing different aspects of cognitive hypotheses. We introduce EasyEEG, a toolbox that includes several multivariate analysis methods to directly test cognitive hypotheses based on topographic responses that include data from all sensors. These multivariate methods can investigate effects in the dimensions of response magnitude and topographic patterns separately using data in the sensor space, therefore enable assessing neural response dynamics. The concise workflow and the modular design provide user-friendly and programmer-friendly features. Users of all levels can benefit from the open-sourced, free EasyEEG to obtain a straightforward solution for efficient processing of EEG data and a complete pipeline from raw data to final results for publication.

Abstract

Neural structures change with age but there is no consensus on the exact processes involved. This study tested the hypothesis that white and grey matter in the language network changes during aging according to a “last in, first out” process. The fractional anisotropy (FA) of white matter and cortical thickness of grey matter were measured in 36 participants whose ages ranged from 55 to 79 years. Within the language network, the dorsal pathway connecting the mid-to-posterior superior temporal cortex (STC) and the inferior frontal cortex (IFC) was affected more by aging in both FA and thickness than the other dorsal pathway connecting the STC with the premotor cortex and the ventral pathway connecting the mid-to-anterior STC with the ventral IFC. These results were independently validated in a second group of 20 participants whose ages ranged from 50 to 73 years. The pathway that is most affected during aging matures later than the other two pathways (which are present at birth). The results are interpreted as showing that the neural structures which mature later are affected more than those that mature earlier, supporting the “last in, first out” theory.

Abstract

Although bilingual speakers are very good at selectively using one language rather than another, sometimes language selection errors occur. To investigate how bilinguals monitor their speech errors and control their languages in use, we recorded event-related potentials (ERPs) in unbalanced Dutch-English bilingual speakers in a cued language-switching task. We tested the conflict-based monitoring model of Nozari and colleagues by investigating the error-related negativity (ERN) and comparing the effects of the two switching directions (i.e., to the first language, L1 vs. to the second language, L2). Results show that the speakers made more language selection errors when switching from their L2 to the L1 than vice versa. In the EEG, we observed a robust ERN effect following language selection errors compared to correct responses, reflecting monitoring of speech errors. Most interestingly, the ERN effect was enlarged when the speakers were switching to their L2 (less conflict) compared to switching to the L1 (more conflict). Our findings do not support the conflict-based monitoring model. We discuss an alternative account in terms of error prediction and reinforcement learning.

Abstract

Although bilingual speakers are very good at selectively using one language rather than another, sometimes language selection errors occur. We examined the relative contribution of top-down cognitive control and bottom-up language priming to these errors. Unbalanced Dutch-English bilinguals named pictures and were cued to switch between languages under time pressure. We also manipulated the number of same-language trials before a switch (long vs. short runs). Results show that speakers made more language selection errors when switching from their second language (L2) to the first language (L1) than vice versa. Furthermore, they made more errors when switching to the L1 after a short compared to a long run of L2 trials. In the reverse switching direction (L1 to L2), run length had no effect. These findings are most compatible with an account of language selection errors that assigns a strong role to top-down processes of cognitive control.

Abstract

It is undisputed that presenting a rhythmic stimulus leads to a measurable brain response that follows the rhythmic structure of this stimulus. What is still debated, however, is the question whether this brain response exclusively reflects a regular repetition of evoked responses, or whether it also includes entrained oscillatory activity. Here we systematically present evidence in favor of an involvement of entrained neural oscillations in the processing of rhythmic input while critically pointing out which questions still need to be addressed before this evidence could be considered conclusive. In this context, we also explicitly discuss the potential functional role of such entrained oscillations, suggesting that these stimulus-aligned oscillations reflect, and serve as, predictive processes, an idea often only implicitly assumed in the literature.

Abstract

For most people, speech production is relatively effortless and error-free. Yet it has long been recognized that we need some type of control over what we are currently saying and what we plan to say. Precisely how we monitor our internal and external speech has been a topic of research interest for several decades. The predominant approach in psycholinguistics has assumed monitoring of both is accomplished via systems responsible for comprehending others' speech.

This special topic aimed to broaden the field, firstly by examining proposals that speech production might also engage more general systems, such as those involved in action monitoring. A second aim was to examine proposals for a production-specific, internal monitor. Both aims require that we also specify the nature of the representations subject to monitoring.

Abstract

Given the limited processing capabilities of the sensory system, it is essential that attended information is gated to downstream areas, whereas unattended information is blocked. While it has been proposed that alpha band (8–13 Hz) activity serves to route information to downstream regions by inhibiting neuronal processing in task-irrelevant regions, this hypothesis remains untested. Here we investigate how neuronal oscillations detected by electroencephalography in visual areas during working memory encoding serve to gate information reflected in the simultaneously recorded blood-oxygenation-level-dependent (BOLD) signals recorded by functional magnetic resonance imaging in downstream ventral regions. We used a paradigm in which 16 participants were presented with faces and landscapes in the right and left hemifields; one hemifield was attended and the other unattended. We observed that decreased alpha power contralateral to the attended object predicted the BOLD signal representing the attended object in ventral object-selective regions. Furthermore, increased alpha power ipsilateral to the attended object predicted a decrease in the BOLD signal representing the unattended object. We also found that the BOLD signal in the dorsal attention network inversely correlated with visual alpha power. This is the first demonstration, to our knowledge, that oscillations in the alpha band are implicated in the gating of information from the visual cortex to the ventral stream, as reflected in the representationally specific BOLD signal. This link of sensory alpha to downstream activity provides a neurophysiological substrate for the mechanism of selective attention during stimulus processing, which not only boosts the attended information but also suppresses distraction. Although previous studies have shown a relation between the BOLD signal from the dorsal attention network and the alpha band at rest, we demonstrate such a relation during a visuospatial task, indicating that the dorsal attention network exercises top-down control of visual alpha activity.