Brain Activation Maps Research Articles

Design Considerations for Long Term Non-invasive Brain Computer Interface Training With Tetraplegic CYBATHLON Pilot.

Several studies in the recent past have demonstrated how Brain Computer Interface (BCI) technology can uncover the neural mechanisms underlying various tasks and translate them into control commands. While a multitude of studies have demonstrated the theoretic potential of BCI, a point of concern is that the studies are still confined to lab settings and mostly limited to healthy, able-bodied subjects. The CYBATHLON 2020 BCI race represents an opportunity to further develop BCI design strategies for use in real-time applications with a tetraplegic end user. In this study, as part of the preparation to participate in CYBATHLON 2020 BCI race, we investigate the design aspects of BCI in relation to the choice of its components, in particular, the type of calibration paradigm and its relevance for long-term use. The end goal was to develop a user-friendly and engaging interface suited for long-term use, especially for a spinal-cord injured (SCI) patient. We compared the efficacy of conventional open-loop calibration paradigms with real-time closed-loop paradigms, using pre-trained BCI decoders. Various indicators of performance were analyzed for this study, including the resulting classification performance, game completion time, brain activation maps, and also subjective feedback from the pilot. Our results show that the closed-loop calibration paradigms with real-time feedback is more engaging for the pilot. They also show an indication of achieving better online median classification performance as compared to conventional calibration paradigms (p = 0.0008). We also observe that stronger and more localized brain activation patterns are elicited in the closed-loop paradigm in which the experiment interface closely resembled the end application. Thus, based on this longitudinal evaluation of single-subject data, we demonstrate that BCI-based calibration paradigms with active user-engagement, such as with real-time feedback, could help in achieving better user acceptability and performance.

Central Processing in Tinnitus: fMRI Study Outlining Patterns of Activation Using an Auditory Discrimination Task in Normal Versus Tinnitus Patients.

Elucidate brain activity differences between patients with tinnitus and controls. Cross-sectional cohort study. Outpatient Otolaryngology clinic. Three cohorts; 8 controls, 12 with subjective idiopathic tinnitus (tinnitus without hearing loss), and 12 with both tinnitus and hearing loss. An auditory oddball identification task was performed in fMRI scanner. Task performance and Tinnitus Handicap Inventory (THI) scores were recorded. Brain activation maps were generated comparing deviant and standard tones as well as at rest. One-way and two-way T-contrasts were generated in addition to multiple regression modeling which identified significant brain regions predicting tinnitus, disease severity, duration, and task performance. Task performance worsened in tinnitus patients with increased auditory workload, in terms of additional hearing loss. THI score and grade correlated with false alarms. The limbic system, heschel's gyrus, angular gyrus and cerebellum have a significant effect on both brain behavior in patients with tinnitus, and predictability of tinnitus and its behavioral implications. Increased auditory workload resulted in poorer task performance. Moreover, it is possible to predict auditory task performance in patients with tinnitus by looking at the activity of specific regions of interest. Heschl's gyrus, angular gyrus, cerebellar, and limbic system activity are important contributors to neurological activity associated with tinnitus. Finally, predictive modeling may influence further research surrounding tinnitus treatment.

Diffusion-informed spatial smoothing of fMRI data in white matter using spectral graph filters

Brain activation mapping using functional magnetic resonance imaging (fMRI) has been extensively studied in brain gray matter (GM), whereas in large disregarded for probing white matter (WM). This unbalanced treatment has been in part due to controversies in relation to the nature of the blood oxygenation level-dependent (BOLD) contrast in WM and its detectability. However, an accumulating body of studies has provided solid evidence of the functional significance of the BOLD signal in WM and has revealed that it exhibits anisotropic spatio-temporal correlations and structure-specific fluctuations concomitant with those of the cortical BOLD signal. In this work, we present an anisotropic spatial filtering scheme for smoothing fMRI data in WM that accounts for known spatial constraints on the BOLD signal in WM. In particular, the spatial correlation structure of the BOLD signal in WM is highly anisotropic and closely linked to local axonal structure in terms of shape and orientation, suggesting that isotropic Gaussian filters conventionally used for smoothing fMRI data are inadequate for denoising the BOLD signal in WM. The fundamental element in the proposed method is a graph-based description of WM that encodes the underlying anisotropy observed across WM, derived from diffusion-weighted MRI data. Based on this representation, and leveraging graph signal processing principles, we design subject-specific spatial filters that adapt to a subject’s unique WM structure at each position in the WM that they are applied at. We use the proposed filters to spatially smooth fMRI data in WM, as an alternative to the conventional practice of using isotropic Gaussian filters. We test the proposed filtering approach on two sets of simulated phantoms, showcasing its greater sensitivity and specificity for the detection of slender anisotropic activations, compared to that achieved with isotropic Gaussian filters. We also present WM activation mapping results on the Human Connectome Project’s 100-unrelated subject dataset, across seven functional tasks, showing that the proposed method enables the detection of streamline-like activations within axonal bundles.

Integrative-omics for discovery of network-level disease biomarkers: a case study in Alzheimer's disease.

A large number of genetic variations have been identified to be associated with Alzheimer's disease (AD) and related quantitative traits. However, majority of existing studies focused on single types of omics data, lacking the power of generating a community including multi-omic markers and their functional connections. Because of this, the immense value of multi-omics data on AD has attracted much attention. Leveraging genomic, transcriptomic and proteomic data, and their backbone network through functional relations, we proposed a modularity-constrained logistic regression model to mine the association between disease status and a group of functionally connected multi-omic features, i.e. single-nucleotide polymorphisms (SNPs), genes and proteins. This new model was applied to the real data collected from the frontal cortex tissue in the Religious Orders Study and Memory and Aging Project cohort. Compared with other state-of-art methods, it provided overall the best prediction performance during cross-validation. This new method helped identify a group of densely connected SNPs, genes and proteins predictive of AD status. These SNPs are mostly expression quantitative trait loci in the frontal region. Brain-wide gene expression profile of these genes and proteins were highly correlated with the brain activation map of 'vision', a brain function partly controlled by frontal cortex. These genes and proteins were also found to be associated with the amyloid deposition, cortical volume and average thickness of frontal regions. Taken together, these results suggested a potential pathway underlying the development of AD from SNPs to gene expression, protein expression and ultimately brain functional and structural changes.

A simple method for implanting free-floating microdevices into the nervous tissue

Objective. Free-floating implantable neural interfaces are an emerging powerful paradigm for mapping and modulation of brain activity. Minuscule wirelessly-powered devices have the potential to provide minimally-invasive interactions with neurons in chronic research and medical applications. However, these devices face a seemingly simple problem—how can they be placed into nervous tissue rapidly, efficiently and in an essentially arbitrary location? Approach. We introduce a novel injection tool and describe a controlled injection approach that minimizes damage to the tissue. Main results. To validate the needle injectable tool and the presented delivery approach, we evaluate the spatial precision and rotational alignment of the microdevices injected into agarose, brain, and sciatic nerve with the aid of tissue clearing and MRI imaging. In this research, we limited the number of injections into the brain to four per rat as we are using microdevices that are designed for an adult head size on a rat model. We then present immunohistology data to assess the damage caused by the needle. Significance. By virtue of its simplicity, the proposed injection method can be used to inject microdevices of all sizes and shapes and will do so in a fast, minimally-invasive, and cost-effective manner. As a result, the introduced technique can be broadly used to accelerate the validation of these next-generation types of electrodes in animal models.

Research on the Experience of Users of Political Slogans in Ukraine

The study partly reveals “Zelenskyi’s phenomenon”, when a person without any political experience confidently won a victory over an experienced politician at the presidential and parliamentary elections. The paper considered neuropsychological understanding of a brand as a multi-modal image with emotional connection and as an artificial addiction. Specific features of the perception of political slogans were studied with EMOTIV Epoc+ 14-channel mobile neurointerface and EmotivPRO and EMOTIV Brain Activity Map software. The ranking of slogans in terms of the efficiency of perception of the individuals of 40-60 years old was carried out on the basis of EEG and the cognitive and emotional indexes: obtained stress, interaction, interest, excitement, concentration, relaxation. The study involved 30 men and 30 women who intended to vote in the presidential elections of 2019. It was established which slogans are the best, good, average, ambiguous, with little effect, ineffective, with a negative effect. It was determined that the most effective and at the same time efficient slogan that evokes emotions and really encourages to support is PRESIDENT IS PEOPLE’S SERVANT. The best slogan that appeals to support it is “We Are Ukraine”, “New Policy of Ukraine”, “Country of Strong People!” The basic cognitive and emotional indexes that would contribute to the creation of effective psychological impact on voters’ behavior are the presence in the slogan of the word “Ukraine”, the avoidance of the so-called “stop words” (for women it is “army” and everything related to violence and death, and for men it is everything related to the provision of material benefits), the use of religious sentimentality in women and gender differences in slogans targeting. The value of the studied phenomenon and the efficiency of slogans and other media products before launching them into mass advertising has been proved.

Incorporation of anatomical MRI knowledge for enhanced mapping of brain metabolism using functional PET

Functional positron emission tomography (fPET) imaging using continuous infusion of [18F]-fluorodeoxyglucose (FDG) is a novel neuroimaging technique to track dynamic glucose utilization in the brain. In comparison to conventional static or dynamic bolus PET, fPET maintains a sustained supply of glucose in the blood plasma which improves sensitivity to measure dynamic glucose changes in the brain, and enables mapping of dynamic brain activity in task-based and resting-state fPET studies. However, there is a trade-off between temporal resolution and spatial noise due to the low concentration of FDG and the limited sensitivity of multi-ring PET scanners. Images from fPET studies suffer from partial volume errors and residual scatter noise that may cause the cerebral metabolic functional maps to be biased. Gaussian smoothing filters used to denoise the fPET images are suboptimal, as they introduce additional partial volume errors. In this work, a post-processing framework based on a magnetic resonance (MR) Bowsher-like prior was used to improve the spatial and temporal signal to noise characteristics of the fPET images. The performance of the MR guided method was compared with conventional denosing methods using both simulated and in vivo task fPET datasets. The results demonstrate that the MR-guided fPET framework denoises the fPET images and improves the partial volume correction, consequently enhancing the sensitivity to identify brain activation, and improving the anatomical accuracy for mapping changes of brain metabolism in response to a visual stimulation task. The framework extends the use of functional PET to investigate the dynamics of brain metabolic responses for faster presentation of brain activation tasks, and for applications in low dose PET imaging.

Keeping the inner voice inside the head, a pilot fMRI study.

IntroductionThe inner voice is experienced during thinking in words (inner speech) and silent reading and evokes brain activity that is highly similar to that associated with external voices. Yet while the inner voice is experienced in internal space (inside the head), external voices (one's own and those of others) are experienced in external space. In this paper, we investigate the neural basis of this differential spatial localization.MethodsWe used fMRI to examine the difference in brain activity between reading silently and reading aloud. As the task involved reading aloud, data were first denoised by removing independent components related to head movement. They were subsequently processed using finite impulse response basis function to address the variations of the hemodynamic response. Final analyses were carried out using permutation‐based statistics, which is appropriate for small samples. These analyses produce spatiotemporal maps of brain activity.ResultsReading silently relative to reading aloud was associated with activity of the “where” auditory pathway (Inferior parietal lobule and middle temporal gyrus), and delayed activity of the primary auditory cortex.ConclusionsThese pilot data suggest that internal space localization of the inner voice depends on the same neural resources as that for external space localization of external voices—the “where” auditory pathway. We discuss the implications of these findings on the possible mechanisms of abnormal experiences of the inner voice as is the case in verbal hallucinations.

Graphene active sensor arrays for long-term and wireless mapping of wide frequency band epicortical brain activity

Graphene active sensors have demonstrated promising capabilities for the detection of electrophysiological signals in the brain. Their functional properties, together with their flexibility as well as their expected stability and biocompatibility have raised them as a promising building block for large-scale sensing neural interfaces. However, in order to provide reliable tools for neuroscience and biomedical engineering applications, the maturity of this technology must be thoroughly studied. Here, we evaluate the performance of 64-channel graphene sensor arrays in terms of homogeneity, sensitivity and stability using a wireless, quasi-commercial headstage and demonstrate the biocompatibility of epicortical graphene chronic implants. Furthermore, to illustrate the potential of the technology to detect cortical signals from infra-slow to high-gamma frequency bands, we perform proof-of-concept long-term wireless recording in a freely behaving rodent. Our work demonstrates the maturity of the graphene-based technology, which represents a promising candidate for chronic, wide frequency band neural sensing interfaces.

Reliability of neural food cue-reactivity in participants with obesity undergoing bariatric surgery: a 26-week longitudinal fMRI study

Obesity is highly prevalent worldwide and results in a high disease burden. The efforts to monitor and predict treatment outcome in participants with obesity using functional magnetic resonance imaging (fMRI) depends on the reliability of the investigated task-fMRI brain activation. To date, no study has investigated whole-brain reliability of neural food cue-reactivity. To close this gap, we analyzed the longitudinal reliability of an established food cue-reactivity task. Longitudinal reliability of neural food-cue-induced brain activation and subjective food craving ratings over three fMRI sessions (T0: 2 weeks before surgery, T1: 8 weeks and T2: 24 weeks after surgery) were investigated in N = 11 participants with obesity. We computed an array of established reliability estimates, including the intraclass correlation (ICC), the Dice and Jaccard coefficients and similarity of brain activation maps. The data indicated good reliability (ICC > 0.6) of subjective food craving ratings over 26 weeks and excellent reliability (ICC > 0.75) of brain activation signals for the contrast of interest (food > neutral) in the caudate, putamen, thalamus, middle cingulum, inferior, middle and superior occipital gyri, and middle and superior temporal gyri and cunei. Using similarity estimates, it was possible to re-identify individuals based on their neural activation maps (73%) with a fading degree of accuracy, when comparing fMRI sessions further apart. The results show excellent reliability of task-fMRI neural brain activation in several brain regions. Current data suggest that fMRI-based measures might indeed be suitable to monitor and predict treatment outcome in participants with obesity undergoing bariatric surgery.

Effects of mild cognitive impairment on brain function during distracted driving

AbstractBackgroundDriving is an integral part of daily life. The complex, multi‐faceted nature of driving makes it vulnerable to the effects of pathological aging on the brain. Studies have shown that patients with mild cognitive impairment (MCI) maintain safe driving in routine circumstances, however there is limited examination of the effects of MCI in more challenging driving scenarios, such as distracted driving. In addition, little is known about how distraction may disrupt the brain networks that are involved in safe driving for patients with MCI. This is the first study to combine functional magnetic resonance imaging (fMRI) with an MRI‐compatible driving simulator to study the effect of distraction on driving‐related brain activity in healthy and MCI cohorts.MethodsThis study used fMRI and an MRI‐compatible driving simulator to measure brain activity during driving in 30 patients with MCI and 30 age and sex‐matched control participants. Patients were diagnosed using the criteria defined by the National Institute on Aging‐Alzheimer’s Association. In the simulator, participants were required to respond to a distracting true or false question while driving. Parametric maps of brain activity were calculated using one‐sample t‐tests, which were cluster‐size thresholded to adjust for multiple comparisons.ResultsBoth groups displayed consistent recruitment of the bilateral frontal, parietal, temporal and occipital lobes during the distracting condition (Figure 1). Patients with MCI exhibited more extensive positive activation in the bilateral superior temporal lobes and the middle and inferior frontal lobes. Although patients with MCI did not commit more driving errors, they displayed impairment by not answering the true or false questions (p < 0.001) and by taking longer to complete turns (p < 0.001).ConclusionsDuring distracted driving, patients with MCI significantly altered their behaviour to safely complete the driving task. The observed increased recruitment of the frontal lobes among patients may be reflective of the compensatory cognitive effort exerted to maintain task performance. MCI may result in changes in driving behaviour, which are exacerbated in challenging driving situations. These findings suggest that subtle changes in measures of driving behaviour may be signs of significant MCI‐related alterations in driving networks of the brain.

Spatially expandable fiber-based probes as a multifunctional deep brain interface

Understanding the cytoarchitecture and wiring of the brain requires improved methods to record and stimulate large groups of neurons with cellular specificity. This requires miniaturized neural interfaces that integrate into brain tissue without altering its properties. Existing neural interface technologies have been shown to provide high-resolution electrophysiological recording with high signal-to-noise ratio. However, with single implantation, the physical properties of these devices limit their access to one, small brain region. To overcome this limitation, we developed a platform that provides three-dimensional coverage of brain tissue through multisite multifunctional fiber-based neural probes guided in a helical scaffold. Chronic recordings from the spatially expandable fiber probes demonstrate the ability of these fiber probes capturing brain activities with a single-unit resolution for long observation times. Furthermore, using Thy1-ChR2-YFP mice we demonstrate the application of our probes in simultaneous recording and optical/chemical modulation of brain activities across distant regions. Similarly, varying electrographic brain activities from different brain regions were detected by our customizable probes in a mouse model of epilepsy, suggesting the potential of using these probes for the investigation of brain disorders such as epilepsy. Ultimately, this technique enables three-dimensional manipulation and mapping of brain activities across distant regions in the deep brain with minimal tissue damage, which can bring new insights for deciphering complex brain functions and dynamics in the near future.

Tomographic Task-Related Functional Near-Infrared Spectroscopy in Acute Sport-Related Concussion: An Observational Case Study.

Making decisions regarding return-to-play after sport-related concussion (SRC) based on resolution of symptoms alone can expose contact-sport athletes to further injury before their recovery is complete. Task-related functional near-infrared spectroscopy (fNIRS) could be used to scan for abnormalities in the brain activation patterns of SRC athletes and help clinicians to manage their return-to-play. This study aims to show a proof of concept of mapping brain activation, using tomographic task-related fNIRS, as part of the clinical assessment of acute SRC patients. A high-density frequency-domain optical device was used to scan 2 SRC patients, within 72 h from injury, during the execution of 3 neurocognitive tests used in clinical practice. The optical data were resolved into a tomographic reconstruction of the brain functional activation pattern, using diffuse optical tomography. Moreover, brain activity was inferred using single-subject statistical analyses. The advantages and limitations of the introduction of this optical technique into the clinical assessment of acute SRC patients are discussed.

Reliability and availability of granger causality density in localization of Rolandic focus in BECTS.

A new method, called granger causality density (GCD), could reflect the directed information flow of the epileptiform activity, which is much closely match with excitatory and inhibitory imbalance theory of epilepsy. Here, we investigated if GCD could effectively localize the Rolandic focus in 50 patients with benign childhood epilepsy with central-temporal spikes (BECTS) from 27 normal children. The BECTS were classified into ictal epileptiform discharges (IEDs; 12 females, 15 males;age, 8.15 ± 1.68years) and non-IEDs (10 females, 13 males; age, 9.09 ± 1.98years) subgroups depending on the presence of central-temporal spikes. Multiple correlation-modality analyses (Pearson, across-voxel and across-subject correlations) were used to calculate the couplings between the GCD maps and IEDs-related brain activation map. The individual lateralization coefficient of localize IEDs and multiple regression analysis were used to identify the reliability of the GCD method in localizing the Rolandic focus. In this study, multiple correlation-modality analyses showed that the IEDs-related brain activation map and the GCD maps had highly temporal (coefficient ׀r\= 0.56 ~ 0.65) and spatial(\r\=0.53~0.91) (r\=~ couplings. The proposed GCD method and multiple regression analyses showed consistentfindings with the clinical EEG recordingsinlateralization of Rolandic focus. Furthermore, the GCD method could reflect the epilepsy-related brain activity during non-IEDs substate. Therefore, the proposed GCD method has the potential to be served as an effective and reliable neuroimaging biomarker to localize the Rolandic focus of BECTS. These findings are critical for clinical early diagnosis, and may promote the progression of treatment and management of pediatric epilepsy.

Regional Hurst Exponent Reflects Impulsivity-Related Alterations in Fronto-Hippocampal Pathways Within the Waiting Impulsivity Network.

In general, the Hurst exponent. is used as a measure of long-term memory of time series. In previous neuroimaging studies, H has been introduced as one important parameter to define resting-state networks, reflecting upon global scale-free properties emerging from a network. H has been examined in the waiting impulsivity (WI) network in an earlier study. We found that alterations of H in the anterior cingulate cortex (HACC) and the nucleus accumbens (HNAcc) were lower in high impulsive (highIMP) compared to low impulsive (lowIMP) participants. Following up on those findings, we addressed the relation between altered fractality in HACC and HNAcc and brain activation and neural network connectivity. To do so, brain activation maps were calculated, and network connectivity was determined using the Dynamic Causal Modeling (DCM) approach. Finally, 1–H scores were determined to quantify the alterations of H. This way, the focus of the analyses was placed on the potential effects of alterations of H on neural network activation and connectivity. Correlation analyses between the alterations of HACC/HNAcc and activation maps and DCM estimates were performed. We found that the alterations of H predominantly correlated with fronto-hippocampal pathways and correlations were significant only in highIMP subjects. For example, alterations of HACC was associated with a decrease in neural activation in the right HC in combination with increased ACC-hippocampal connectivity. Alteration inHNAcc, in return, was related to an increase in bilateral prefrontal activation in combination with increased fronto-hippocampal connectivity. The findings, that the WI network was related to H alteration in highIMP subjects indicated that impulse control was not reduced per se but lacked consistency. Additionally, H has been used to describe long-term memory processes before, e.g., in capital markets, energy future prices, and human memory. Thus, current findings supported the relation of H toward memory processing even when further prominent cognitive functions were involved.

Monkeying with the piano

Neuroscience The anatomical organization of auditory cortical pathways in nonhuman primates (NHPs) shows remarkable similarities with humans. So why don't NHPs have a more speech-like communication system? Archakov et al. trained macaques to perform an auditory-motor task using a purpose-built piano. Mapping brain activity by functional magnetic resonance imaging showed that sound sequences activated the auditory midbrain and cortex. More importantly, sound sequences that had been learned by self-production also activated motor cortex and basal ganglia. This shows that monkeys can form auditory-motor links and that this is not the reason why they do not speak. Instead, the origin of speech in humans may have required the evolution of a command apparatus that controls the upper vocal tract. Proc. Natl. Acad. Sci. U.S.A. 117 , 15242 (2020).

Flexible use of allocentric and egocentric spatial memories activates differential neural networks in mice

Goal-directed navigation can be based on world-centered (allocentric) or body-centered (egocentric) representations of the environment, mediated by a wide network of interconnected brain regions, including hippocampus, striatum and prefrontal cortex. The relative contribution of these regions to navigation from novel or familiar routes, that demand a different degree of flexibility in the use of the stored spatial representations, has not been completely explored. To address this issue, we trained mice to find a reward relying on allocentric or egocentric information, in a modified version of the cross-maze task. Then we used Zif268 expression to map brain activation when well-trained mice were required to find the goal from a novel or familiar location. Successful navigation was correlated with the activation of CA1, posterior-dorsomedial striatum, nucleus accumbens core and infralimbic cortex when allocentric-trained mice needed to use a novel route. Allocentric navigation from a familiar route activated dorsomedial striatum, nucleus accumbens, prelimbic and infralimbic cortex. None of the structures analyzed was significantly activated in egocentric-trained mice, irrespective of the starting position. These data suggest that a flexible use of stored allocentric information, that allows goal finding even from a location never explored during training, induces a shift from fronto-striatal to hippocampal circuits.

Low-frequency transcranial stimulation of pre-supplementary motor area alleviates levodopa-induced dyskinesia in Parkinson's disease: a randomized cross-over trial.

Levodopa-induced dyskinesia gradually emerges during long-term dopamine therapy, causing major disability in patients with Parkinson disease. Using pharmacodynamic functional MRI, we have previously shown that the intake of levodopa triggers an excessive activation of the pre-supplementary motor area in Parkinson disease patients with peak-of-dose dyskinesia. In this pre-registered, interventional study, we tested whether the abnormal responsiveness of the pre-supplementary motor area to levodopa may constitute a ‘stimulation target’ for treating dyskinesia. A gender-balanced group of 17 Parkinson disease patients with peak-of-dose dyskinesia received 30 min of robot-assisted repetitive transcranial magnetic stimulation, after they had paused their anti-Parkinson medication. Real-repetitive transcranial magnetic stimulation at 100% or sham-repetitive transcranial magnetic stimulation at 30% of individual resting corticomotor threshold of left first dorsal interosseous muscle was applied on separate days in counterbalanced order. Following repetitive transcranial magnetic stimulation, patients took 200 mg of oral levodopa and underwent functional MRI to map brain activity, while they performed the same go/no-go task as in our previous study. Blinded video assessment revealed that real-repetitive transcranial magnetic stimulation delayed the onset of dyskinesia and reduced its severity relative to sham-repetitive transcranial magnetic stimulation. Individual improvement in dyskinesia severity scaled linearly with the modulatory effect of real-repetitive transcranial magnetic stimulation on task-related activation in the pre-supplementary motor area. Stimulation-induced delay in dyskinesia onset correlated positively with the induced electrical field strength in the pre-supplementary motor area. Our results provide converging evidence that the levodopa-triggered increase in pre-supplementary motor area activity plays a causal role in the pathophysiology of peak-of-dose dyskinesia and constitutes a promising cortical target for brain stimulation therapy.

Dynamic Brain Responses Modulated by Precise Timing Prediction in an Opposing Process.

The brain function of prediction is fundamental for human beings to shape perceptions efficiently and successively. Through decades of effort, a valuable brain activation map has been obtained for prediction. However, much less is known about how the brain manages the prediction process over time using traditional neuropsychological paradigms. Here, we implemented an innovative paradigm for timing prediction to precisely study the temporal dynamics of neural oscillations. In the experiment recruiting 45 participants, expectation suppression was found for the overall electroencephalographic activity, consistent with previous hemodynamic studies. Notably, we found that N1 was positively associated with predictability while N2 showed a reversed relation to predictability. Furthermore, the matching prediction had a similar profile with no timing prediction, both showing an almost saturated N1 and an absence of N2. The results indicate that the N1 process showed a 'sharpening' effect for predictable inputs, while the N2 process showed a 'dampening' effect. Therefore, these two paradoxical neural effects of prediction, which have provoked wide confusion in accounting for expectation suppression, actually co-exist in the procedure of timing prediction but work in separate time windows. These findings strongly support a recently-proposed opposing process theory.

Auditory representation of learned sound sequences in motor regions of the macaque brain

Human speech production requires the ability to couple motor actions with their auditory consequences. Nonhuman primates might not have speech because they lack this ability. To address this question, we trained macaques to perform an auditory-motor task producing sound sequences via hand presses on a newly designed device ("monkey piano"). Catch trials were interspersed to ascertain the monkeys were listening to the sounds they produced. Functional MRI was then used to map brain activity while the animals listened attentively to the sound sequences they had learned to produce and to two control sequences, which were either completely unfamiliar or familiar through passive exposure only. All sounds activated auditory midbrain and cortex, but listening to the sequences that were learned by self-production additionally activated the putamen and the hand and arm regions of motor cortex. These results indicate that, in principle, monkeys are capable of forming internal models linking sound perception and production in motor regions of the brain, so this ability is not special to speech in humans. However, the coupling of sounds and actions in nonhuman primates (and the availability of an internal model supporting it) seems not to extend to the upper vocal tract, that is, the supralaryngeal articulators, which are key for the production of speech sounds in humans. The origin of speech may have required the evolution of a "command apparatus" similar to the control of the hand, which was crucial for the evolution of tool use.