Brain activity underlying auditory perceptual learning during short period training: simultaneous fMRI and EEG recording

Individual differences in working memory impact the trajectory of non-native speech category learning

What is the role of working memory over the course of non-native speech category learning? Prior work has predominantly focused on how working memory might influence learning assessed at a single timepoint. Here, we substantially extend this prior work by examining the role of working memory on speech learning performance over time (i.e., over several months) and leverage a multifaceted approach that provides key insights into how working memory influences learning accuracy, maintenance of knowledge over time, generalization ability, and decision processes. We found that the role of working memory in non-native speech learning depends on the timepoint of learning and whether individuals learned the categories at all. Among learners, across all stages of learning, working memory was associated with higher accuracy as well as faster and slightly more cautious decision making. Further, while learners and non-learners did not have substantially different working memory performance, learners had faster evidence accumulation and more cautious decision thresholds throughout all sessions. Working memory may enhance learning by facilitating rapid category acquisition in initial stages and enabling faster and slightly more careful decision-making strategies that may reduce the overall effort needed to learn. Our results have important implications for developing interventions to improve learning in naturalistic language contexts.

Slowed reaction times in cognitive fatigue are not attributable to declines in motor preparation

Cognitive fatigue (CF) can result from sustained mental effort, is characterized by subjective feelings of exhaustion and cognitive performance deficits, and is associated with slowed simple reaction time (RT). This study determined whether declines in motor preparation underlie this RT effect. Motor preparation level was indexed using simple RT and the StartReact effect, wherein a prepared movement is involuntarily triggered at short latency by a startling acoustic stimulus (SAS). It was predicted that if decreased motor preparation underlies CF-associated RT increases, then an attenuated StartReact effect would be observed following cognitive task completion. Subjective fatigue assessment and a simple RT task were performed before and after a cognitively fatiguing task or non-fatiguing control intervention. On 25% of RT trials, a SAS replaced the go-signal to assess the StartReact effect. CF inducement was verified by significant declines in cognitive performance (p = 0.003), along with increases in subjective CF (p < 0.001) and control RT (p = 0.018) following the cognitive fatigue intervention, but not the control intervention. No significant pre-to-post-test changes in SAS RT were observed, indicating that RT increases resulting from CF are not substantially associated with declines in motor preparation, and instead may be attributable to other stages of processing during a simple RT task.

Behavioural performance improvement in visuomotor learning correlates with functional and microstructural brain changes

A better understanding of practice-induced functional and structural changes in our brains can help us design more effective learning environments that provide better outcomes. Although there is growing evidence from human neuroimaging that experience-dependent brain plasticity is expressed in measurable brain changes that are correlated with behavioural performance, the relationship between behavioural performance and structural or functional brain changes, and particularly the time course of these changes, is not well characterised. To understand the link between neuroplastic changes and behavioural performance, 15 healthy participants in this study followed a systematic eye movement training programme for 30 min daily at home, 5 days a week and for 6 consecutive weeks. Behavioural performance statistics and eye tracking data were captured throughout the training period to evaluate learning outcomes. Imaging data (DTI and fMRI) were collected at baseline, after two and six weeks of continuous training, and four weeks after training ended. Participants showed significant improvements in behavioural performance (faster task completion time, lower fixation number and fixation duration). Spatially overlapping reductions in microstructural diffusivity measures (MD, AD and RD) and functional activation increases (BOLD signal) were observed in two main areas: extrastriate visual cortex (V3d) and the frontal part of the cerebellum/Fastigial Oculomotor Region (FOR), which are both involved in visual processing. An increase of functional activity was also recorded in the right frontal eye field. Behavioural, structural and functional changes were correlated. Microstructural change is a better predictor for long-term behavioural change than functional activation is, whereas the latter is superior in predicting instantaneous performance. Structural and functional measures at week 2 of the training programme also predict performance at week 6 and 10, which suggests that imaging data at an early stage of training may be useful in optimising practice environments or rehabilitative training programmes.

Enhanced Brain Network Activity in Complex Movement Rhythms: A Simultaneous Functional Magnetic Resonance Imaging and Electroencephalography Study

Generating movement rhythms is known to involve a network of distributed brain regions associated with motor planning, control, execution, and perception of timing for the repertoire of motor actions. What brain areas are bound in the network and how the network activity is modulated by rhythmic complexity have not been completely explored. To contribute to answering these questions, we designed a study in which nine healthy participants performed simple to complex rhythmic finger movement tasks while undergoing simultaneous functional magnetic resonance imaging and electroencephalography (fMRI-EEG) recordings of their brain activity during the tasks and rest. From fMRI blood oxygenation-level-dependent (BOLD) measurements, we found that the complexity of rhythms was associated with brain activations in the primary motor cortex (PMC), supplementary motor area (SMA), and cerebellum (Cb), and with network interactions from these cortical regions to the cerebellum. The spectral analysis of single-trial EEG source waveforms at the cortical regions further showed that there were bidirectional interactions between PMC and SMA, and the complexity of rhythms was associated with power spectra and Granger causality spectra in the beta (13-30 Hz) frequency band, not in the alpha (8-12 Hz) and gamma (30-58 Hz) bands. These results provide us new insights into the mechanisms for movement rhythm complexity.

A review on EEG-based methods for screening and diagnosing alcohol use disorder

The screening test for alcohol use disorder (AUD) patients has been of subjective nature and could be misleading in particular cases such as a misreporting the actual quantity of alcohol intake. Although the neuroimaging modality such as electroencephalography (EEG) has shown promising research results in achieving objectivity during the screening and diagnosis of AUD patients. However, the translation of these findings for clinical applications has been largely understudied and hence less clear. This study advocates the use of EEG as a diagnostic and screening tool for AUD patients that may help the clinicians during clinical decision making. In this context, a comprehensive review on EEG-based methods is provided including related electrophysiological techniques reported in the literature. More specifically, the EEG abnormalities associated with the conditions of AUD patients are summarized. The aim is to explore the potentials of objective techniques involving quantities/features derived from resting EEG, event-related potentials or event-related oscillations data.

Perceptual Plasticity for Auditory Object Recognition

In our auditory environment, we rarely experience the exact acoustic waveform twice. This is especially true for communicative signals that have meaning for listeners. In speech and music, the acoustic signal changes as a function of the talker (or instrument), speaking (or playing) rate, and room acoustics, to name a few factors. Yet, despite this acoustic variability, we are able to recognize a sentence or melody as the same across various kinds of acoustic inputs and determine meaning based on listening goals, expectations, context, and experience. The recognition process relates acoustic signals to prior experience despite variability in signal-relevant and signal-irrelevant acoustic properties, some of which could be considered as "noise" in service of a recognition goal. However, some acoustic variability, if systematic, is lawful and can be exploited by listeners to aid in recognition. Perceivable changes in systematic variability can herald a need for listeners to reorganize perception and reorient their attention to more immediately signal-relevant cues. This view is not incorporated currently in many extant theories of auditory perception, which traditionally reduce psychological or neural representations of perceptual objects and the processes that act on them to static entities. While this reduction is likely done for the sake of empirical tractability, such a reduction may seriously distort the perceptual process to be modeled. We argue that perceptual representations, as well as the processes underlying perception, are dynamically determined by an interaction between the uncertainty of the auditory signal and constraints of context. This suggests that the process of auditory recognition is highly context-dependent in that the identity of a given auditory object may be intrinsically tied to its preceding context. To argue for the flexible neural and psychological updating of sound-to-meaning mappings across speech and music, we draw upon examples of perceptual categories that are thought to be highly stable. This framework suggests that the process of auditory recognition cannot be divorced from the short-term context in which an auditory object is presented. Implications for auditory category acquisition and extant models of auditory perception, both cognitive and neural, are discussed.

Experience-dependent modulation of alpha and beta during action observation and motor imagery

Background

EEG studies investigating the neural networks that facilitate action observation (AO) and kinaesthetic motor imagery (KMI) have shown reduced, or desynchronized, power in the alpha (8–12 Hz) and beta (13–30 Hz) frequency bands relative to rest, reflecting efficient activation of task-relevant areas. Functional modulation of these networks through expertise in dance has been established using fMRI, with greater activation among experts during AO. While there is evidence for experience-dependent plasticity of alpha power during AO of dance, the influence of familiarity on beta power during AO, and alpha and beta activity during KMI, remain unclear. The purpose of the present study was to measure the impact of familiarity on confidence ratings and EEG activity during (1) AO of a brief ballet sequence, (2) KMI of this same sequence, and (3) KMI of non-dance movements among ballet dancers, dancers from other genres, and non-dancers.

Results

Ballet dancers highly familiar with the genre of the experimental stimulus demonstrated higher individual alpha peak frequency (iAPF), greater alpha desynchronization, and greater task-related beta power during AO, as well as faster iAPF during KMI of non-dance movements. While no between-group differences in alpha or beta power were observed during KMI of dance or non-dance movements, all participants showed significant desynchronization relative to baseline, and further desynchronization during dance KMI relative to non-dance KMI indicative of greater cognitive load.

Conclusions

These findings confirm and extend evidence for experience-dependent plasticity of alpha and beta activity during AO of dance and KMI. We also provide novel evidence for modulation of iAPF that is faster when tuned to the specific motor repertoire of the observer. By considering the multiple functional roles of these frequency bands during the same task (AO), we have disentangled the compounded contribution of familiarity and expertise to alpha desynchronization for mediating task engagement among familiar ballet dancers and reflecting task difficulty among unfamiliar non-dance subjects, respectively. That KMI of a complex dance sequence relative to everyday, non-dance movements recruits greater cognitive resources suggests it may be a more powerful tool in driving neural plasticity of action networks, especially among the elderly and those with movement disorders.

Inhibitor effect of paricalcitol in rat model of pentylenetetrazol-induced seizures

Vitamin D has various systemic effects on bone metabolism, modulation of the immune system, stabilization of the cell membrane, oxidative stress, inflammation, apoptosis, and various other hormones. Differing from active vitamin D, paricalcitol is a relatively safe VDR agonist due to its relatively few side effects. This study has investigated the anticonvulsant effect of paricalcitol in convulsions induced by pentylenetetrazole (PTZ). 36 male Sprague-Dawley rats were divided randomly into two groups: 18 for EEG recording (PTZ 35 mg/kg) and 18 for behavioral studies (PTZ 70 mg/kg). Forty-five minutes before the PTZ injection, both groups of rats were given 5 and 10 μg/kg of paricalcitol i.p., respectively. Racine convulsion scores, first myoclonic jerk time, spike percentages, and antioxidant status were evaluated in the groups. Our results showed that the Racine's Convulsion Scale (RCS) score significantly dropped in the paricalcitol-treated group, analysis of the first myoclonic jerk (FMJ) latencies demonstrated a significantly longer latency in the paricalcitol-applied group, and spike percentages at EEG recordings significantly decreased with paricalcitol. Moreover, MDA levels were lower and SOD activity were higher in the 5 μg/kg paricalcitol group compared to the saline group; these results were more prominent in 10 μg/kg paricalcitol group. Our study has demonstrated that paricalcitol has protective effects on PTZ-induced convulsions. Based on the SOD and MDA levels in our study, these effects may result from the antioxidant characteristics of paricalcitol.

Simultaneous EEG-fMRI for working memory of the human brain

Memory plays an important role in human life. Memory can be divided into two categories, i.e., long term memory and short term memory (STM). STM or working memory (WM) stores information for a short span of time and it is used for information manipulations and fast response activities. WM is generally involved in the higher cognitive functions of the brain. Different studies have been carried out by researchers to understand the WM process. Most of these studies were based on neuroimaging modalities like fMRI, EEG, MEG etc., which use standalone processes. Each neuroimaging modality has some pros and cons. For example, EEG gives high temporal resolution but poor spatial resolution. On the other hand, the fMRI results have a high spatial resolution but poor temporal resolution. For a more in depth understanding and insight of what is happening inside the human brain during the WM process or during cognitive tasks, high spatial as well as high temporal resolution is desirable. Over the past decade, researchers have been working to combine different modalities to achieve a high spatial and temporal resolution at the same time. Developments of MRI compatible EEG equipment in recent times have enabled researchers to combine EEG-fMRI successfully. The research publications in simultaneous EEG-fMRI have been increasing tremendously. This review is focused on the WM research involving simultaneous EEG-fMRI data acquisition and analysis. We have covered the simultaneous EEG-fMRI application in WM and data processing. Also, it adds to potential fusion methods which can be used for simultaneous EEG-fMRI for WM and cognitive tasks.

Dynamic changes in network activations characterize early learning of a natural language

Those who are initially exposed to an unfamiliar language have difficulty separating running speech into individual words, but over time will recognize both words and the grammatical structure of the language. Behavioral studies have used artificial languages to demonstrate that humans are sensitive to distributional information in language input, and can use this information to discover the structure of that language. This is done without direct instruction and learning occurs over the course of minutes rather than days or months. Moreover, learners may attend to different aspects of the language input as their own learning progresses. Here, we examine processing associated with the early stages of exposure to a natural language, using fMRI. Listeners were exposed to an unfamiliar language (Icelandic) while undergoing four consecutive fMRI scans. The Icelandic stimuli were constrained in ways known to produce rapid learning of aspects of language structure. After approximately 4 min of exposure to the Icelandic stimuli, participants began to differentiate between correct and incorrect sentences at above chance levels, with significant improvement between the first and last scan. An independent component analysis of the imaging data revealed four task-related components, two of which were associated with behavioral performance early in the experiment, and two with performance later in the experiment. This outcome suggests dynamic changes occur in the recruitment of neural resources even within the initial period of exposure to an unfamiliar natural language.

How learning to abstract shapes neural sound representations

The transformation of acoustic signals into abstract perceptual representations is the essence of the efficient and goal-directed neural processing of sounds in complex natural environments. While the human and animal auditory system is perfectly equipped to process the spectrotemporal sound features, adequate sound identification and categorization require neural sound representations that are invariant to irrelevant stimulus parameters. Crucially, what is relevant and irrelevant is not necessarily intrinsic to the physical stimulus structure but needs to be learned over time, often through integration of information from other senses. This review discusses the main principles underlying categorical sound perception with a special focus on the role of learning and neural plasticity. We examine the role of different neural structures along the auditory processing pathway in the formation of abstract sound representations with respect to hierarchical as well as dynamic and distributed processing models. Whereas most fMRI studies on categorical sound processing employed speech sounds, the emphasis of the current review lies on the contribution of empirical studies using natural or artificial sounds that enable separating acoustic and perceptual processing levels and avoid interference with existing category representations. Finally, we discuss the opportunities of modern analyses techniques such as multivariate pattern analysis (MVPA) in studying categorical sound representations. With their increased sensitivity to distributed activation changes—even in absence of changes in overall signal level—these analyses techniques provide a promising tool to reveal the neural underpinnings of perceptually invariant sound representations.

Selective adaptation to "oddball" sounds by the human auditory system

Adaptation to both common and rare sounds has been independently reported in neurophysiological studies using probabilistic stimulus paradigms in small mammals. However, the apparent sensitivity of the mammalian auditory system to the statistics of incoming sound has not yet been generalized to task-related human auditory perception. Here, we show that human listeners selectively adapt to novel sounds within scenes unfolding over minutes. Listeners' performance in an auditory discrimination task remains steady for the most common elements within the scene but, after the first minute, performance improves for distinct and rare (oddball) sound elements, at the expense of rare sounds that are relatively less distinct. Our data provide the first evidence of enhanced coding of oddball sounds in a human auditory discrimination task and suggest the existence of an adaptive mechanism that tracks the long-term statistics of sounds and deploys coding resources accordingly.