Predictive motor activation: Modulated by expectancy or predictability?

Predicting actions is a fundamental ability that helps us to comprehend what is happening in our environment and to interact with others. The motor system was previously identified as source of action predictions. Yet, which aspect of the statistical likelihood of upcoming actions the motor system is sensitive to remains an open question. This EEG study investigated how regularities in observed actions are reflected in the motor system and utilized to predict upcoming actions. Prior to measuring EEG, participants watched videos of action sequences with different transitional probabilities. After training, participants' brain activity over motor areas was measured using EEG while watching videos of action sequences with the same statistical structure. Focusing on the mu and beta frequency bands we tested whether activity of the motor system reflects the statistical likelihood of upcoming actions. We also explored two distinct aspects of the statistical structure that capture different prediction processes, expectancy and predictability. Expectancy describes participants' expectation of the most likely action, whereas predictability represents all possible actions and their relative probabilities. Results revealed that mu and beta oscillations play different roles during action prediction. While the mu rhythm reflected anticipatory activity without any link to the statistical structure, the beta rhythm was related to the expectancy of an action. Our findings support theories proposing that the motor system underlies action prediction, and they extend such theories by showing that multiple forms of statistical information are extracted when observing action sequences. This information is integrated in the prediction generated by the neural motor system of which action is going to happen next.

Spectral signature of attentional reorienting in the human brain

As we move in the environment, attention shifts to novel objects of interest based on either their sensory salience or behavioral value (reorienting). This study measures with magnetoencephalography (MEG) different properties (amplitude, onset-to-peak duration) of event-related desynchronization/synchronization (ERD/ERS) of oscillatory activity during a visuospatial attention task designed to separate activity related to reorienting vs. maintaining attention to the same location, controlling for target detection and response processes. The oscillatory activity was measured both in fMRI-defined regions of interest (ROIs) of the dorsal attention (DAN) and visual (VIS) networks, previously defined as task-relevant in the same subjects, or whole-brain in a pre-defined set of cortical ROIs encompassing the main brain networks. Reorienting attention (shift cues) as compared to maintaining attention (stay cues) produced a temporal sequence of ERD/ERS modulations at multiple frequencies in specific anatomical regions/networks. An early (∼330 ms), stronger, transient theta ERS occurred in task-relevant (DAN, VIS) and control networks (VAN, CON, FPN), possibly reflecting an alert/reset signal in response to the cue. A more sustained, behaviorally relevant, low-beta band ERD peaking ∼450 ms following shift cues (∼410 for stay cues) localized in frontal and parietal regions of the DAN. This modulation is consistent with a control signal re-routing information across visual hemifields. Contralateral vs. ipsilateral shift cues produced in occipital visual regions a stronger, sustained alpha ERD (peak ∼470 ms) and a longer, transient high beta/gamma ERS (peak ∼490 ms) related to preparatory visual modulations in advance of target occurrence. This is the first description of a cascade of oscillatory processes during attentional reorienting in specific anatomical regions and networks. Among these processes, a behaviorally relevant beta desynchronization in the FEF is likely associated with the control of attention shifts.

Prefrontal oscillations modulate the propagation of neuronal activity required for working memory

Cognition involves using attended information, maintained in working memory (WM), to guide action. During a cognitive task, a correct response requires flexible, selective gating so that only the appropriate information flows from WM to downstream effectors that carry out the response. In this work, we used biophysically-detailed modeling to explore the hypothesis that network oscillations in prefrontal cortex (PFC), leveraging local inhibition, can independently gate responses to items in WM. The key role of local inhibition was to control the period between spike bursts in the outputs, and to produce an oscillatory response no matter whether the WM item was maintained in an asynchronous or oscillatory state. We found that the WM item that induced an oscillatory population response in the PFC output layer with the shortest period between spike bursts was most reliably propagated. The network resonant frequency (i.e., the input frequency that produces the largest response) of the output layer can be flexibly tuned by varying the excitability of deep layer principal cells. Our model suggests that experimentally-observed modulation of PFC beta-frequency (15-30 Hz) and gamma-frequency (30-80 Hz) oscillations could leverage network resonance and local inhibition to govern the flexible routing of signals in service to cognitive processes like gating outputs from working memory and the selection of rule-based actions. Importantly, we show for the first time that nonspecific changes in deep layer excitability can tune the output gate's resonant frequency, enabling the specific selection of signals encoded by populations in asynchronous or fast oscillatory states. More generally, this represents a dynamic mechanism by which adjusting network excitability can govern the propagation of asynchronous and oscillatory signals throughout neocortex.

Comparing MEG and EEG in detecting the ~20-Hz rhythm modulation to tactile and proprioceptive stimulation

Modulation of the ~20-Hz brain rhythm has been used to evaluate the functional state of the sensorimotor cortex both in healthy subjects and patients, such as stroke patients. The ~20-Hz brain rhythm can be detected by both magnetoencephalography (MEG) and electroencephalography (EEG), but the comparability of these methods has not been evaluated. Here, we compare these two methods in the evaluating of ~20-Hz activity modulation to somatosensory stimuli. Rhythmic ~20-Hz activity during separate tactile and proprioceptive stimulation of the right and left index finger was recorded simultaneously with MEG and EEG in twenty-four healthy participants. Both tactile and proprioceptive stimulus produced a clear suppression at 300-350 ​ms followed by a subsequent rebound at 700-900 ​ms after stimulus onset, detected at similar latencies both with MEG and EEG. The relative amplitudes of suppression and rebound correlated strongly between MEG and EEG recordings. However, the relative strength of suppression and rebound in the contralateral hemisphere (with respect to the stimulated hand) was significantly stronger in MEG than in EEG recordings. Our results indicate that MEG recordings produced signals with higher signal-to-noise ratio than EEG, favoring MEG as an optimal tool for studies evaluating sensorimotor cortical functions. However, the strong correlation between MEG and EEG results encourages the use of EEG when translating studies to clinical practice. The clear advantage of EEG is the availability of the method in hospitals and bed-side measurements at the acute phase.

Triad TMS of the human motor cortex

Usually, cortical rhythmic activities are studied with local field potentials. To overcome small amplitude of EEGs easily disturbed by several factors, we developed a new method to study motor cortical rhythm using Motor evoked potentials (MEPs) to transcranial magnetic stimulation (TMS). We, here, review triad-conditioning TMS technique for investigating the intrinsic rhythm of the human primary motor cortex (M1). MEP was recorded from the first dorsal interosseous muscle (FDI). TMS was applied over the M1 to study its frequency dependency. In the intervention condition, the subthreshold, same intensity three conditioning stimuli separated by a certain interval were given prior to the supra-threshold test stimulus. In the control condition, the test stimulus was given alone. MEPs were compared between the two conditions. In healthy volunteers, triad-conditioning stimulus (TCS) at an interval of 25 ms induced MEP facilitation, whereas the other intervals TCS induced no facilitation. This frequency dependent facilitation may reflect some intrinsic rhythm of M1 (25 ms, i.e. 40 Hz). In cortical myoclonus, the 40 ms TCS induced facilitation whereas 25 ms TCS induced no facilitation, which is consistent with abnormal rhythm of M1 at 25 Hz (40 ms interval) reported previously. In Parkinson's disease (PD), 25 ms TCS evoked no facilitation. Triad-conditioning TMS may enable us to investigate the intrinsic rhythmic activity of M1 and its abnormality.

Neuroimaging Study of Alpha and Beta EEG Biofeedback Effects on Neural Networks

Neural networks interaction was studied in healthy men (20-35 years old) who underwent 20 sessions of EEG biofeedback training outside the MRI scanner, with concurrent fMRI-EEG scans at the beginning, middle, and end of the course. The study recruited 35 subjects for EEG biofeedback, but only 18 of them were considered as "successful" in self-regulation of target EEG bands during the whole course of training. Results of fMRI analysis during EEG biofeedback are reported only for these "successful" trainees. The experimental group (N = 23 total, N = 13 "successful") upregulated the power of alpha rhythm, while the control group (N = 12 total, N = 5 "successful") beta rhythm, with the protocol instructions being as for alpha training in both. The acquisition of the stable skills of alpha self-regulation was followed by the weakening of the irrelevant links between the cerebellum and visuospatial network (VSN), as well as between the VSN, the right executive control network (RECN), and the cuneus. It was also found formation of a stable complex based on the interaction of the precuneus, the cuneus, the VSN, and the high level visuospatial network (HVN), along with the strengthening of the interaction of the anterior salience network (ASN) with the precuneus. In the control group, beta enhancement training was accompanied by weakening of interaction between the precuneus and the default mode network, and a decrease in connectivity between the cuneus and the primary visual network (PVN). The differences between the alpha training group and the control group increased successively during training. Alpha training was characterized by a less pronounced interaction of the network formed by the PVN and the HVN, as well as by an increased interaction of the cerebellum with the precuneus and the RECN. The study demonstrated the differences in the structure and interaction of neural networks involved into alpha and beta generating systems forming and functioning, which should be taken into account during planning neurofeedback interventions. Possibility of using fMRI-guided biofeedback organized according to the described neural networks interaction may advance more accurate targeting specific symptoms during neurotherapy.

Subthalamic oscillatory activity and connectivity during gait in Parkinson's disease

Local field potentials (LFP) of the subthalamic nucleus (STN) recorded during walking may provide clues for determining the function of the STN during gait and also, may be used as biomarker to steer adaptive brain stimulation devices. Here, we present LFP recordings from an implanted sensing neurostimulator (Medtronic Activa PC + S) during walking and rest with and without stimulation in 10 patients with Parkinson's disease and electrodes placed bilaterally in the STN. We also present recordings from two of these patients recorded with externalized leads. We analyzed changes in overall frequency power, bilateral connectivity, high beta frequency oscillatory characteristics and gait-cycle related oscillatory activity. We report that deep brain stimulation improves gait parameters. High beta frequency power (20-30 Hz) and bilateral oscillatory connectivity are reduced during gait, while the attenuation of high beta power is absent during stimulation. Oscillatory characteristics are affected in a similar way. We describe a reduction in overall high beta burst amplitude and burst lifetimes during gait as compared to rest off stimulation. Investigating gait cycle related oscillatory dynamics, we found that alpha, beta and gamma frequency power is modulated in time during gait, locked to the gait cycle. We argue that these changes are related to movement induced artifacts and that these issues have important implications for similar research.

A gradient of frequency-dependent synaptic properties along the longitudinal hippocampal axis

Background

The hippocampus is a functionally heterogeneous brain structure and specializations of the intrinsic neuronal network may crucially support the functional segregation along the longitudinal axis of the hippocampus. Short-term synaptic plasticity plays fundamental roles in information processing and may be importantly involved in diversifying the properties of local neuronal network along the hippocampus long axis. Therefore, we aimed to examine the properties of the cornu ammonis 1 (CA1) synapses along the entire dorsoventral axis of the rat hippocampus using field excitatory postsynaptic potentials from transverse rat hippocampal slices and a frequency stimulation paradigm.

Results

Applying a ten-pulse stimulus train at frequencies from 0.1 to 100 Hz to the Schaffer collaterals we found a gradually diversified pattern of frequency-dependent synaptic effects along the dorsoventral hippocampus axis. The first conditioned response was facilitated along the whole hippocampus for stimulus frequencies 10–40 Hz. However, steady-state responses or averaged responses generally ranged from maximum synaptic facilitation in the most dorsal segment of the hippocampus to maximum synaptic depression in the most ventral segment of the hippocampus. In particular, dorsal synapses facilitated for stimulus frequency up to 50 Hz while they depressed at higher frequencies (75–100 Hz). Facilitation at dorsal synapses was maximal at stimulus frequency of 20 Hz. On the contrary, the most ventral synapses showed depression regardless of the stimulus frequency, only displaying a transient facilitation at the beginning of 10–50 Hz stimulation. Importantly, the synapses in the medial hippocampus displayed a transitory behavior. Finally, as a whole the hippocampal synapses maximally facilitated at 20 Hz and increasingly depressed at 50–100 Hz.

Conclusion

The short-term synaptic dynamics change gradually along the hippocampal long axis in a frequency-dependent fashion conveying distinct properties of information processing to successive segments of the structure, thereby crucially supporting functional segregation along the dorsoventral axis of the hippocampus.

Higher similarity in beta topography between tasks than subjects

We have recently provided evidence for highly idiosyncratic topographic distributions of beta oscillations (as well as slow potentials) across individuals. More recently, by emphasizing the analysis of similarity instead of differences across tasks, we concluded that differences between an attention task and quiet resting may be negligible or at least unsystematic across subjects. Due to the possibility that individual differences could be due to noise in a wide sense or some inherent instability of beta activity, we designed a replication study to explicitly test whether pairs of individuals matched for head size and shape would still present less similar beta topography than each individual between sessions or tasks. We used independent component analysis (ICA) for an exhaustive decomposition of beta activity in a visual attention task and in quiet resting, recorded by 256-channel EEG in 20 subjects, on two separate days. We evaluated whether each ICA component obtained in one task and in one given individual could be explained by a linear regression model based on the topographic patterns of the complementary task (correlation between one component with a linear combination of components from complementary conditions), of the same task in a second session and of a matched individual. Results again showed a high topographic similarity between conditions, as previously seen between reasoning and simple visual attention beta correlates. From an overall number of 16 components representing brain activity obtained for the tasks (out of 60 originally computed where the remaining were considered noise), over 92% could satisfactorily be explained by the complementary task. Although the similarity between sessions was significantly smaller than between tasks on each day, the similarity between sessions was statistically higher than that between subjects in a highly significant way. We discuss the possible biases of group spatial averaging and the emphasis on differences as opposed to similarities, and noise in a wide sense, as the main causes of hardly replicable findings on task-related forms of activity and the inconclusive state of a universal functional mapping of cortical association areas.

EEG-neurofeedback training of beta band (12-22Hz) affects alpha and beta frequencies - A controlled study of a healthy population

The frequency-function relation of various EEG bands has inspired EEG-neurofeedback procedures intending to improve cognitive abilities in numerous clinical groups. In this study, we administered EEG-neurofeedback (EEG-NFB) to a healthy population to determine the efficacy of this procedure. We evaluated feedback manipulation in the beta band (12-22Hz), known to be involved in visual attention processing. Two groups of healthy adults were trained to either up- or down-regulate beta band activity, thus providing mutual control. Up-regulation training induced increases in beta and alpha band (8-12Hz) amplitudes during the first three sessions. Group-independent increases in the activity of both bands were observed in the later phase of training. EEG changes were not matched by measured behavioural indices of attention. Parallel changes in the two bands challenge the idea of frequency-specific EEG-NFB protocols and suggest their interdependence. Our study exposes the possibility (i) that the alpha band is more prone to manipulation, and (ii) that changes in the bands' amplitudes are independent from specified training. We therefore encourage a more comprehensive approach to EEG-neurofeedback training embracing physiological and/or operational relations among various EEG bands.

TRPC3 channels play a critical role in the theta component of pilocarpine-induced status epilepticus in mice

OBJECTIVE

Canonical transient receptor potential (TRPC) channels constitute a family of cation channels that exhibit a regional and cell-specific expression pattern throughout the brain. It has been reported previously that TRPC3 channels are effectors of the brain-derived neurotrophic factor (BDNF)/trkB signaling pathway. Given the long postulated role of BDNF in epileptogenesis, TRPC3 channels may be a critical component in the underlying pathophysiology of seizure and epilepsy. In this study, we investigated the precise role of TRPC3 channels in pilocarpine-induced status epilepticus (SE).

METHODS

The role of TRPC3 channels was investigated using TRPC3 knockout (KO) mice and TRPC3-selective inhibitor Pyr3. Video and electroencephalography (EEG) recording of pilocarpine-induced seizures were performed.

RESULTS

We found that genetic ablation of TRPC3 channels reduces behavioral manifestations of seizures and the root-mean-square (RMS) power of SE, indicating a significant contribution of TRPC3 channels to pilocarpine-induced SE. Furthermore, the reduction in SE in TRPC3KO mice is caused by a selective attenuation of pilocarpine-induced theta activity, which dominates both the preictal phase and SE phase. Pyr3 also caused a reduction in the overall RMS power of pilocarpine-induced SE and a selective reduction in the theta activity during SE.

SIGNIFICANCE

Our results demonstrate that TRPC3 channels unequivocally contribute to pilocarpine-induced SE and could be a novel molecular target for new anticonvulsive drugs.

Sleep fragmentation alters brain energy metabolism without modifying hippocampal electrophysiological response to novelty exposure

Sleep is viewed as a fundamental restorative function of the brain, but its specific role in neural energy budget remains poorly understood. Sleep deprivation dampens brain energy metabolism and impairs cognitive functions. Intriguingly, sleep fragmentation, despite normal total sleep duration, has a similar cognitive impact, and in this paper we ask the question of whether it may also impair brain energy metabolism. To this end, we used a recently developed mouse model of 2 weeks of sleep fragmentation and measured 2-deoxy-glucose uptake and glycogen, glucose and lactate concentration in different brain regions. In order to homogenize mice behaviour during metabolic measurements, we exposed them to a novel environment for 1 h. Using an intra-hippocampal electrode, we first showed that hippocampal electroencephalograph (EEG) response to exploration was unaltered by 1 or 14 days of sleep fragmentation. However, after 14 days, sleep fragmented mice exhibited a lower uptake of 2-deoxy-glucose in cortex and hippocampus and lower cortical lactate levels than control mice. Our results suggest that long-term sleep fragmentation impaired brain metabolism to a similar extent as total sleep deprivation without affecting the neuronal responsiveness of hippocampus to a novel environment.

The effects of elevated endogenous GABA levels on movement-related network oscillations

The EEG/MEG signal is generated primarily by the summation of the post-synaptic potentials of cortical principal cells. At a microcircuit level, these glutamatergic principal cells are reciprocally connected to GABAergic interneurons and cortical oscillations are thought to be dependent on the balance of excitation and inhibition between these cell types. To investigate the dependence of movement-related cortical oscillations on excitation-inhibition balance, we pharmacologically manipulated the GABA system using tiagabine, which blocks GABA Transporter 1(GAT-1), the GABA uptake transporter and increases endogenous GABA activity. In a blinded, placebo-controlled, crossover design, in 15 healthy participants we administered either 15mg of tiagabine or a placebo. We recorded whole-head magnetoencephalograms, while the participants performed a movement task, prior to, one hour post, three hour post and five hour post tiagabine ingestion. Using time-frequency analysis of beamformer source reconstructions, we quantified the baseline level of beta activity (15-30Hz), the post-movement beta rebound (PMBR), beta event-related desynchronisation (beta-ERD) and movement-related gamma synchronisation (MRGS) (60-90Hz). Our results demonstrated that tiagabine, and hence elevated endogenous GABA levels causes, an elevation of baseline beta power, enhanced beta-ERD and reduced PMBR, but no modulation of MRGS. Comparing our results to recent literature (Hall et al., 2011) we suggest that beta-ERD may be a GABAA receptor mediated process while PMBR may be GABAB receptor mediated.