A parietal–frontal network studied by somatosensory oddball MEG responses, and its cross-modal consistency

A multimodal cortical network of sensory expectation violation revealed by fMRI

The brain is subjected to multi-modal sensory information in an environment governed by statistical dependencies. Mismatch responses (MMRs), classically recorded with EEG, have provided valuable insights into the brain's processing of regularities and the generation of corresponding sensory predictions. Only few studies allow for comparisons of MMRs across multiple modalities in a simultaneous sensory stream and their corresponding cross-modal context sensitivity remains unknown. Here, we used a tri-modal version of the roving stimulus paradigm in fMRI to elicit MMRs in the auditory, somatosensory and visual modality. Participants (N = 29) were simultaneously presented with sequences of low and high intensity stimuli in each of the three senses while actively observing the tri-modal input stream and occasionally reporting the intensity of the previous stimulus in a prompted modality. The sequences were based on a probabilistic model, defining transition probabilities such that, for each modality, stimuli were more likely to repeat (p = .825) than change (p = .175) and stimulus intensities were equiprobable (p = .5). Moreover, each transition was conditional on the configuration of the other two modalities comprising global (cross-modal) predictive properties of the sequences. We identified a shared mismatch network of modality general inferior frontal and temporo-parietal areas as well as sensory areas, where the connectivity (psychophysiological interaction) between these regions was modulated during mismatch processing. Further, we found deviant responses within the network to be modulated by local stimulus repetition, which suggests highly comparable processing of expectation violation across modalities. Moreover, hierarchically higher regions of the mismatch network in the temporo-parietal area around the intraparietal sulcus were identified to signal cross-modal expectation violation. With the consistency of MMRs across audition, somatosensation and vision, our study provides insights into a shared cortical network of uni- and multi-modal expectation violation in response to sequence regularities.

Magnetoencephalography reveals impaired sensory gating and change detection in older adults in the somatosensory system

Brain electrophysiological responses can provide information about age-related decline in sensory-cognitive functions with high temporal accuracy. Studies have revealed impairments in early sensory gating and pre-attentive change detection mechanisms in older adults, but no magnetoencephalographic (MEG) studies have been undertaken into both non-attentive and attentive somatosensory functions and their relationship to ageing. Magnetoencephalography was utilized to record cortical somatosensory brain responses in young (20-28 yrs), middle-aged (46-56 yrs), and older adults (64-78 yrs) under active and passive somatosensory oddball conditions. A repeated standard stimulus was occasionally replaced by a deviant stimulus (p = .1), which was an electrical pulse on a different finger. We examined the amplitudes of M50 and M100 responses reflecting sensory gating, and later components reflecting change detection and attention shifting (M190 and M250 for the passive condition, and M200 and M350 for the active condition, respectively). Spatiotemporal cluster-based permutation tests revealed that older adults had significantly larger M100 component amplitudes than young adults for task-irrelevant stimuli in both passive and active condition. Older adults also showed a reduced M250 component and an altered M350 in response to deviant stimuli. The responses of middle-aged adults did not differ from those of younger adults, but this study should be repeated with a larger sample size. By demonstrating changes in both somatosensory gating and attentional shifting mechanisms, our findings extend previous research on the effects of ageing on pre-attentive and attentive brain functions.

Double dissociation between P300 components and task switch error type in healthy but not psychosis participants

Event-related potentials (ERPs) during oddball tasks and the behavioral performance on the Penn Conditional Exclusion Task (PCET) measure context-appropriate responding: P300 ERPs to oddball targets reflect detection of input changes and context updating in working memory, and PCET performance indexes detection, adherence, and maintenance of mental set changes. More specifically, PCET variables quantify cognitive functions including inductive reasoning (set 1 completion), mental flexibility (perseverative errors), and working memory maintenance (regressive errors). Past research showed that both P300 ERPs and PCET performance are disrupted in psychosis. This study probed the possible neural correlates of 3 PCET abnormalities that occur in participants with psychosis via the overlapping cognitive demands of the two study paradigms. In a two-tiered analysis, psychosis (n = 492) and healthy participants (n = 244) were first divided based on completion of set 1 - which measures subjects' ability to use inductive reasoning to arrive at the correct set. Results showed that participants who failed set 1 produced lower parietal P300, independent of clinical status. In the second tier of analysis, a double dissociation was found among healthy set 1 completers: frontal P300 amplitudes were negatively associated with perseverative errors, and parietal P300 was negatively associated with regressive errors. In contrast, psychosis participants showed global P300 reductions regardless of PCET performance. From this we conclude that in psychosis, overall activations evoked by the oddball task are reduced while the cognitive functions required by PCET are still somewhat supported, showing some level of independence or compensatory physiology in psychosis between neural activities underlying the two tasks.

Neural dynamics of illusory tactile pulling sensations

Directional tactile pulling sensations are integral to everyday life, but their neural mechanisms remain unknown. Prior accounts hold that primary somatosensory (SI) activity is sufficient to generate pulling sensations, with alternative proposals suggesting that amodal frontal or parietal regions may be critical. We combined high-density EEG with asymmetric vibration, which creates an illusory pulling sensation, thereby unconfounding pulling sensations from unrelated sensorimotor processes. Oddballs that created opposite direction pulls to common stimuli were compared to the same oddballs after neutral common stimuli (symmetric vibration) and to neutral oddballs. We found evidence against the sensory-frontal N140 and in favor of the midline P200 tracking the emergence of pulling sensations, specifically contralateral parietal lobe activity 264-320ms, centered on the intraparietal sulcus. This suggests that SI is not sufficient to generate pulling sensations, which instead depend on the parietal association cortex, and may reflect the extraction of orientation information and related spatial processing.

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Tactile pulling sensations are difficult to isolate in the human brain

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Illusory pulls from asymmetric vibration allow neural activity to be isolated

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Pulling sensations are driven by parietal lobe activity 264-320ms post-stimulus

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Spatial processing in the parietal lobe may be essential for pulling sensations

Reconfiguration of Cortical Brain Network from Searching to Spotting for Dynamic Visual Targets

BACKGROUND

Detecting dynamic targets from complex visual scenes is an important problem in real world. However, the cognitive mechanism accounting for dynamic visual target detection remains unclear.

NEW METHOD

Herein, we aim to explore the cognitive process of dynamic visual target detection from searching to spotting and provide more concrete evidence for cognitive studies related to target detection. Cortical source responses with high spatiotemporal resolution were reconstructed from scalp EEG signals. Then, time-varying cortical networks were built using adaptive directed transfer function to explore the cognitive processes while detecting the dynamic visual target.

RESULTS

The experimental results demonstrated that the dynamic visual target detection enhanced the activation in both the visual and attention networks. Specially, the information flow from the middle occipital gyrus (MOG) mainly contributed to the position function, whereas the activation of the prefrontal cortex (PFC) reflected spatial attention maintenance.

CONCLUSION

The left "frontal-central-parietal" network played as a leading information source in dynamic target detection tasks. These findings provide new insights into cognitive processes of dynamic visual target detection.

DATA AVAILABILITY STATEMENT

The datasets in this study are available on request to the corresponding author.

Magnetoencephalography Responses to Unpredictable and Predictable Rare Somatosensory Stimuli in Healthy Adult Humans

Mismatch brain responses to unpredicted rare stimuli are suggested to be a neural indicator of prediction error, but this has rarely been studied in the somatosensory modality. Here, we investigated how the brain responds to unpredictable and predictable rare events. Magnetoencephalography responses were measured in adults frequently presented with somatosensory stimuli (FRE) that were occasionally replaced by two consecutively presented rare stimuli [unpredictable rare stimulus (UR) and predictable rare stimulus (PR); p = 0.1 for each]. The FRE and PR were electrical stimulations administered to either the little finger or the forefinger in a counterbalanced manner between the two conditions. The UR was a simultaneous electrical stimulation to both the forefinger and the little finger (for a smaller subgroup, the UR and FRE were counterbalanced for the stimulus properties). The grand-averaged responses were characterized by two main components: one at 30-100 ms (M55) and the other at 130-230 ms (M150) latency. Source-level analysis was conducted for the primary somatosensory cortex (SI) and the secondary somatosensory cortex (SII). The M55 responses were larger for the UR and PR than for the FRE in both the SI and the SII areas and were larger for the UR than for the PR. For M150, both investigated areas showed increased activity for the UR and the PR compared to the FRE. Interestingly, although the UR was larger in stimulus energy (stimulation of two fingers at the same time) and had a larger prediction error potential than the PR, the M150 responses to these two rare stimuli did not differ in source strength in either the SI or the SII area. The results suggest that M55, but not M150, can possibly be associated with prediction error signals. These findings highlight the need for disentangling prediction error and rareness-related effects in future studies investigating prediction error signals.

Magnetoencephalography Signal Processing, Forward Modeling, Magnetoencephalography Inverse Source Imaging, and Coherence Analysis

Magnetoencephalography (MEG) is a noninvasive functional imaging technique for the brain. MEG directly measures the magnetic signal due to neuronal activation in gray matter with high spatial localization accuracy. The first part of this article covers the overall concepts of MEG and the forward and inverse modeling techniques. It is followed by examples of analyzing evoked and resting-state MEG signals using a high-resolution MEG source imaging technique. Next, different techniques for connectivity and network analysis are reviewed with examples showing connectivity estimates from resting-state and epileptic activity.

Neural surprise in somatosensory Bayesian learning

Tracking statistical regularities of the environment is important for shaping human behavior and perception. Evidence suggests that the brain learns environmental dependencies using Bayesian principles. However, much remains unknown about the employed algorithms, for somesthesis in particular. Here, we describe the cortical dynamics of the somatosensory learning system to investigate both the form of the generative model as well as its neural surprise signatures. Specifically, we recorded EEG data from 40 participants subjected to a somatosensory roving-stimulus paradigm and performed single-trial modeling across peri-stimulus time in both sensor and source space. Our Bayesian model selection procedure indicates that evoked potentials are best described by a non-hierarchical learning model that tracks transitions between observations using leaky integration. From around 70ms post-stimulus onset, secondary somatosensory cortices are found to represent confidence-corrected surprise as a measure of model inadequacy. Indications of Bayesian surprise encoding, reflecting model updating, are found in primary somatosensory cortex from around 140ms. This dissociation is compatible with the idea that early surprise signals may control subsequent model update rates. In sum, our findings support the hypothesis that early somatosensory processing reflects Bayesian perceptual learning and contribute to an understanding of its underlying mechanisms.

Our environment features statistical regularities, such as a drop of rain predicting imminent rainfall. Despite the importance for behavior and survival, much remains unknown about how these dependencies are learned, particularly for somatosensation. As surprise signalling about novel observations indicates a mismatch between one’s beliefs and the world, it has been hypothesized that surprise computation plays an important role in perceptual learning. By analyzing EEG data from human participants receiving sequences of tactile stimulation, we compare different formulations of surprise and investigate the employed underlying learning model. Our results indicate that the brain estimates transitions between observations. Furthermore, we identified different signatures of surprise computation and thereby provide a dissociation of the neural correlates of belief inadequacy and belief updating. Specifically, early surprise responses from around 70ms were found to signal the need for changes to the model, with encoding of its subsequent updating occurring from around 140ms. These results provide insights into how somatosensory surprise signals may contribute to the learning of environmental statistics.

Modulations of Insular Projections by Prior Belief Mediate the Precision of Prediction Error during Tactile Learning

Awareness for surprising sensory events is shaped by prior belief inferred from past experience. Here, we combined hierarchical Bayesian modeling with fMRI on an associative learning task in 28 male human participants to characterize the effect of the prior belief of tactile events on connections mediating the outcome of perceptual decisions. Activity in anterior insular cortex (AIC), premotor cortex (PMd), and inferior parietal lobule (IPL) were modulated by prior belief on unexpected targets compared with expected targets. On expected targets, prior belief decreased the connection strength from AIC to IPL, whereas it increased the connection strength from AIC to PMd when targets were unexpected. Individual differences in the modulatory strength of prior belief on insular projections correlated with the precision that increases the influence of prediction errors on belief updating. These results suggest complementary effects of prior belief on insular-frontoparietal projections mediating the precision of prediction during probabilistic tactile learning.SIGNIFICANCE STATEMENT In a probabilistic environment, the prior belief of sensory events can be inferred from past experiences. How this prior belief modulates effective brain connectivity for updating expectations for future decision-making remains unexplored. Combining hierarchical Bayesian modeling with fMRI, we show that during tactile associative learning, prior expectations modulate connections originating in the anterior insula cortex and targeting salience-related and attention-related frontoparietal areas (i.e., parietal and premotor cortex). These connections seem to be involved in updating evidence based on the precision of ascending inputs to guide future decision-making.

Performing various perceptual actions elicits differentiable P300 responses

Several studies have explored the differentiation of visual action verbs (e.g., see, perceive, and notice). The vast number and variety to choose from, along with a common understanding between the meanings of the words, suggests that they may represent measurable differences in perceptual processing. The present study investigated how manipulating the visual action verb embedded into a common instruction could produce either differentiable electrophysiological or behavioral effects, or possibly both. It was hypothesized that the P300 component elicited during an oddball task would differ depending on the visual action that participants had been instructed to perform. Results support this hypothesis, but suggest that response bias also could contribute to action performance. When participants were asked to 'sense' deviants in an oddball task, the P300 differed in amplitude compared to when they were asked to 'distinguish' the deviants. In addition, participants displayed varying response times for the instructions 'notice' versus 'view', 'distinguish' versus 'sense', and 'notice' versus 'sense'. When considering the behavioral and ERP results together, we can conclude that response biases and perceptual cognitive processing both contribute to how identical stimuli can be processed depending on the visual action performed.

Distinguishing the Visual Working Memory Training and Practice Effects by the Effective Connectivity During n-back Tasks: A DCM of ERP Study

Visual working memory (WM) training and practice can result in improved task performance and increased P300 amplitude; however, only training can yield N160 enhancements. N160 amplitudes are related to the spatial attention, the detection of novelty and the inhibitory control, while P300 amplitudes are related to the selective attention. Therefore, it could be speculated that the mechanisms underlying N160 and P300 production may differ to accommodate to their functions. Based on the different N160 engagements and different functional roles of N160 and P300, we hypothesized that the effects of visual WM training and practice can be dissociated by their brain effective connectivity patterns. We compared different neural connectivity configurations for the main task-related brain activities including N160 and P300 during the visual three-back task in subjects after visual WM training (the WM group) and after repetitive task practice (the control group). The behavioral result shows significantly greater improvement in accuracy after training and suggests that visual WM training can boost the learning process of this simple task. The N160 peak amplitude increased significantly after training over the anterior and posterior brain areas but decreased after practice over the posterior areas, indicating different mechanisms for mediating the training and practice effects. In support of our hypothesis, we observed that visual WM training alters the frontal-parietal connections, which comprise the executive control network (ECN) and the dorsal attention network (DAN), whereas practice modulates the parietal-frontal connections underpinning P300 production for selective attention. It should be noted that the analytic results in this study are conditional on the plausible models being tested and the experimental settings. Studies that employ different tasks, devices and plausible models may lead to different results. Nevertheless, our findings provide a reference for distinguishing the visual WM training and practice effects by the underlying neuroplasticity.

The somatosensory mismatch negativity as a window into body representations in infancy

How the body is represented in the developing brain is a topic of growing interest. The current study takes a novel approach to investigating neural body representations in infants by recording somatosensory mismatch negativity (sMMN) responses elicited by tactile stimulation of different body locations. Recent research in adults has suggested that sMMN amplitude may be influenced by the relative distance between representations of the stimulated body parts in somatosensory cortex. The current study uses a similar paradigm to explore whether the sMMN can be elicited in infants, and to test whether the infant sMMN response is sensitive to the somatotopic organization of somatosensory cortex. Participants were healthy infants (n = 31) aged 6 and 7 months. The protocol leveraged a discontinuity in cortical somatotopic organization, whereby the representations of the neck and the face are separated by representations of the arms, the hands and the shoulder. In a double-deviant oddball protocol, stimulation of the hand (100 trials, 10% probability) and neck (100 trials, 10% probability) was interspersed among repeated stimulation of the face (800 trials, 80% probability). Waveforms showed evidence of an infant sMMN response that was significantly larger for the face/neck contrast than for the face/hand contrast. These results suggest that, for certain combinations of body parts, early pre-attentive tactile discrimination in infants may be influenced by distance between the corresponding cortical representations. The results provide the first evidence that the sMMN can be elicited in infants, and pave the way for further applications of the sMMN in studying body representations in preverbal infants.

Interactive Sonification Exploring Emergent Behavior Applying Models for Biological Information and Listening

Sonification is an open-ended design task to construct sound informing a listener of data. Understanding application context is critical for shaping design requirements for data translation into sound. Sonification requires methodology to maintain reproducibility when data sources exhibit non-linear properties of self-organization and emergent behavior. This research formalizes interactive sonification in an extensible model to support reproducibility when data exhibits emergent behavior. In the absence of sonification theory, extensibility demonstrates relevant methods across case studies. The interactive sonification framework foregrounds three factors: reproducible system implementation for generating sonification; interactive mechanisms enhancing a listener's multisensory observations; and reproducible data from models that characterize emergent behavior. Supramodal attention research suggests interactive exploration with auditory feedback can generate context for recognizing irregular patterns and transient dynamics. The sonification framework provides circular causality as a signal pathway for modeling a listener interacting with emergent behavior. The extensible sonification model adopts a data acquisition pathway to formalize functional symmetry across three subsystems: Experimental Data Source, Sound Generation, and Guided Exploration. To differentiate time criticality and dimensionality of emerging dynamics, tuning functions are applied between subsystems to maintain scale and symmetry of concurrent processes and temporal dynamics. Tuning functions accommodate sonification design strategies that yield order parameter values to render emerging patterns discoverable as well as rehearsable, to reproduce desired instances for clinical listeners. Case studies are implemented with two computational models, Chua's circuit and Swarm Chemistry social agent simulation, generating data in real-time that exhibits emergent behavior. Heuristic Listening is introduced as an informal model of a listener's clinical attention to data sonification through multisensory interaction in a context of structured inquiry. Three methods are introduced to assess the proposed sonification framework: Listening Scenario classification, data flow Attunement, and Sonification Design Patterns to classify sound control. Case study implementations are assessed against these methods comparing levels of abstraction between experimental data and sound generation. Outcomes demonstrate the framework performance as a reference model for representing experimental implementations, also for identifying common sonification structures having different experimental implementations, identifying common functions implemented in different subsystems, and comparing impact of affordances across multiple implementations of listening scenarios.

Using somatosensory mismatch responses as a window into somatotopic processing of tactile stimulation

Brain responses to tactile stimulation have often been studied through the examination of ERPs elicited to touch on the body surface. Here, we examined two factors potentially modulating the amplitude of the somatosensory mismatch negativity (sMMN) and P300 responses elicited by touch to pairs of body parts: (a) the distance between the representation of these body parts in somatosensory cortex, and (b) the physical distances between the stimulated points on the body surface. The sMMN and the P300 response were elicited by tactile stimulation in two oddball protocols. One protocol leveraged a discontinuity in cortical somatotopic organization, and involved stimulation of either the neck or the hand in relation to stimulation of the lip. The other protocol involved stimulation to the third or fifth finger in relation to the second finger. The neck-lip pairing resulted in significantly larger sMMN responses (with shorter latencies) than the hand-lip pairing, whereas the reverse was true for the amplitude of the P300. Mean sMMN amplitude and latency did not differ between finger pairings. However, larger P300 responses were elicited to stimulation of the fifth finger than the third finger. These results suggest that, for certain combinations of body parts, early automatic somatosensory mismatch responses may be influenced by distance between the cortical representations of these body parts, whereas the later P300 response may be more influenced by the distance between stimulated body parts on the body surface. Future investigations can shed more light on this novel suggestion.

Neural Basis of Early Somatosensory Change Detection: A Magnetoencephalography Study

The mismatch negativity (MMN) reflects the early detection of changes in sensory stimuli at the cortical level. The mechanisms underlying its genesis remain debated. This magnetoencephalography study investigates the spatio-temporal dynamics and the neural mechanisms of the magnetic somatosensory MMN. Somatosensory evoked magnetic fields elicited by tactile stimulation of the right fingertip (Single), tactile stimulation of the right middle phalanx and fingertip (Double) or omissions (Omitted) of tactile stimuli were studied in different paradigms: in oddballs where Double/Omitted followed a sequence of four Single, in sequences of two stimuli where Double occurred after one Single, and in random presentation of Double only. The predictability of Double occurrence in oddballs was also manipulated. Cortical sources of evoked responses were identified using equivalent current dipole modeling. Evoked responses elicited by Double were significantly different from those elicited by Single at the contralateral secondary somatosensory (cSII) cortex. Double elicited higher cSII cortex responses than Single when preceded by a sequence of four Single, compared to when they were preceded by one Single. Double elicited higher cSII cortex response when presented alone compared to when Double were preceded by one or a sequence of Single. Omitted elicited similar cSII cortex response than Single. Double in oddballs led to higher cSII cortex responses when less predictable. These data suggest that early tactile change detection involves mainly cSII cortex. The predictive coding framework probably accounts for the SII cortex response features observed in the different tactile paradigms.

Development of advanced signal processing and source imaging methods for superparamagnetic relaxometry

Superparamagnetic relaxometry (SPMR) is a highly sensitive technique for the in vivo detection of tumor cells and may improve early stage detection of cancers. SPMR employs superparamagnetic iron oxide nanoparticles (SPION). After a brief magnetizing pulse is used to align the SPION, SPMR measures the time decay of SPION using super-conducting quantum interference device (SQUID) sensors. Substantial research has been carried out in developing the SQUID hardware and in improving the properties of the SPION. However, little research has been done in the pre-processing of sensor signals and post-processing source modeling in SPMR. In the present study, we illustrate new pre-processing tools that were developed to: (1) remove trials contaminated with artifacts, (2) evaluate and ensure that a single decay process associated with bounded SPION exists in the data, (3) automatically detect and correct flux jumps, and (4) accurately fit the sensor signals with different decay models. Furthermore, we developed an automated approach based on multi-start dipole imaging technique to obtain the locations and magnitudes of multiple magnetic sources, without initial guesses from the users. A regularization process was implemented to solve the ambiguity issue related to the SPMR source variables. A procedure based on reduced chi-square cost-function was introduced to objectively obtain the adequate number of dipoles that describe the data. The new pre-processing tools and multi-start source imaging approach have been successfully evaluated using phantom data. In conclusion, these tools and multi-start source modeling approach substantially enhance the accuracy and sensitivity in detecting and localizing sources from the SPMR signals. Furthermore, multi-start approach with regularization provided robust and accurate solutions for a poor SNR condition similar to the SPMR detection sensitivity in the order of 1000 cells. We believe such algorithms will help establishing the industrial standards for SPMR when applying the technique in pre-clinical and clinical settings.

Hemispheric lateralization of resting-state functional connectivity of the ventral striatum: an exploratory study

Resting-state functional connectivity (rsFC) is widely used to examine cerebral functional organization. The ventral striatum (VS) is critical to motivated behavior, with extant studies suggesting functional hemispheric asymmetry. The current work investigated differences in rsFC between the left (L) and right (R) VS and explored gender differences in the extent of functional lateralization. In 106 adults, we computed a laterality index (fcLI) to query whether a target region shows greater or less connectivity to the L vs R VS. A total of 45 target regions with hemispheric masks were examined from the Automated Anatomic Labeling atlas. One-sample t test was performed to explore significant laterality in the whole sample and in men and women separately. Two-sample t test was performed to examine gender differences in fcLI. At a corrected threshold (p < 0.05/45 = 0.0011), the dorsomedial prefrontal cortex (dmPFC) and posterior cingulate cortex (pCC) showed L lateralization and the intraparietal sulcus (IPS) and supramarginal gyrus (SMG) showed R lateralization in VS connectivity. Except for the pCC, these findings were replicated in a different data set (n = 97) from the Human Connectome Project. Furthermore, the fcLI of VS-pCC was negatively correlated with a novelty seeking trait in women but not in men. Together, the findings may suggest a more important role of the L VS in linking saliency response to self control and other internally directed processes. Right lateralization of VS connectivity to the SMG and IPS may support attention and action directed to external behavioral contingencies.

Multilevel Cortical Processing of Somatosensory Novelty: A Magnetoencephalography Study

Using magnetoencephalography (MEG), this study investigates the spatio-temporal dynamics of the multilevel cortical processing of somatosensory change detection. Neuromagnetic signals of 16 healthy adult subjects (7 females and 9 males, mean age 29 ± 3 years) were recorded using whole-scalp-covering MEG while they underwent an oddball paradigm based on simple standard (right index fingertip tactile stimulation) and deviant (simultaneous right index fingertip and middle phalanx tactile stimulation) stimuli gathered into sequences to create and then deviate from stimulus patterns at multiple (local vs. global) levels of complexity. Five healthy adult subjects (3 females and 2 males, mean age 31, 6 ± 2 years) also underwent a similar oddball paradigm in which standard and deviant stimuli were flipped. Local deviations led to a somatosensory mismatch response peaking at 55-130 ms post-stimulus onset with a cortical generator located at the contralateral secondary somatosensory (cSII) cortex. The mismatch response was independent of the deviant stimuli physical characteristics. Global deviants led to a P300 response with cortical sources located bilaterally at temporo-parietal junction (TPJ) and supplementary motor area (SMA). The posterior parietal cortex (PPC) and the SMA were found to generate a contingent magnetic variation (CMV) attributed to top-down expectations. Amplitude of mismatch responses were modulated by top-down expectations and correlated with both the magnitude of the CMV and the P300 amplitude at the right TPJ. These results provide novel empirical evidence for a unified sensory novelty detection system in the human brain by linking detection of salient sensory stimuli in personal and extra-personal spaces to a common framework of multilevel cortical processing.

Anterior insula coordinates hierarchical processing of tactile mismatch responses

The body underlies our sense of self, emotion, and agency. Signals arising from the skin convey warmth, social touch, and the physical characteristics of external stimuli. Surprising or unexpected tactile sensations can herald events of motivational salience, including imminent threats (e.g., an insect bite) and hedonic rewards (e.g., a caressing touch). Awareness of such events is thought to depend upon the hierarchical integration of body-related mismatch responses by the anterior insula. To investigate this possibility, we measured brain activity using functional magnetic resonance imaging, while healthy participants performed a roving tactile oddball task. Mass-univariate analysis demonstrated robust activations in limbic, somatosensory, and prefrontal cortical areas previously implicated in tactile deviancy, body awareness, and cognitive control. Dynamic Causal Modelling revealed that unexpected stimuli increased the strength of forward connections along a caudal to rostral hierarchy-projecting from thalamic and somatosensory regions towards insula, cingulate and prefrontal cortices. Within this ascending flow of sensory information, the AIC was the only region to show increased backwards connectivity to the somatosensory cortex, augmenting a reciprocal exchange of neuronal signals. Further, participants who rated stimulus changes as easier to detect showed stronger modulation of descending PFC to AIC connections by deviance. These results suggest that the AIC coordinates hierarchical processing of tactile prediction error. They are interpreted in support of an embodied predictive coding model where AIC mediated body awareness is involved in anchoring a global neuronal workspace.

The Time-Varying Networks in P300: A Task-Evoked EEG Study

P300 is an important event-related potential that can be elicited by external visual, auditory, and somatosensory stimuli. Various cognition-related brain functions (i.e., attention, intelligence, and working memory) and multiple brain regions (i.e., prefrontal, frontal, and parietal) are reported to be involved in the elicitation of P300. However, these studies do not investigate the instant interactions across the neural cortices from the hierarchy of milliseconds. Importantly, time-varying network analysis among these brain regions can uncover the detailed and dynamic information processing in the corresponding cognition process. In the current study, we utilize the adaptive directed transfer function to construct the time-varying networks of P300 based on scalp electroencephalographs, investigating the time-varying information processing in P300 that can depict the deeper neural mechanism of P300 from the network. Our analysis found that different stages of P300 evoked different brain networks, i.e., the center area performs as the central source during the decision process stage, while the source region is transferred to the right prefrontal cortex (rPFC) in the neuronal response stage. Moreover, during the neuronal response stage, the directed information that flows from the rPFC to the parietal cortex are remarkably important. These findings indicate that the two brain hemispheres exhibit asymmetrical functions in processing related information for different P300 stages, and this work may provide new evidence for our better understanding of the neural mechanism of P300 generation.

Mastication accelerates Go/No-go decisional processing: An event-related potential study

OBJECTIVE

The purpose of the present study was to investigate the effect of mastication on Go/No-go decisional processing using event-related potentials (ERPs).

METHOD

Thirteen normal subjects underwent seven sessions of a somatosensory Go/No-go paradigm for approximately 4min; Pre, and Post 1, 2, 3, 4, 5, and 6. The Control condition included the same seven sessions. The RT and standard deviation were recorded, and the peak amplitude and latency of the N140 and P300 components were analyzed.

RESULTS

The RT was significantly shorter in Mastication than in Control at Post 1-3 and 4-6. The peak latency of N140 was earlier in Mastication than in Control at Post 4-6. The latency of N140 was shortened by repeated sessions in Mastication, but not by those in Control. The peak latency of P300 was significantly shorter in Mastication than in Control at Post 4-6. The peak latency of P300 was significantly longer in Control with repeated sessions, but not in Mastication.

CONCLUSIONS

These results suggest that mastication may influence response execution processing in Go trials, as well as response inhibition processing in No-go trials.

SIGNIFICANCE

Mastication accelerated Go/No-go decisional processing in the human brain.

Neuronal correlates of a virtual-reality-based passive sensory P300 network

P300, a positive event-related potential (ERP) evoked at around 300 ms after stimulus, can be elicited using an active or passive oddball paradigm. Active P300 requires a person’s intentional response, whereas passive P300 does not require an intentional response. Passive P300 has been used in incommunicative patients for consciousness detection and brain computer interface. Active and passive P300 differ in amplitude, but not in latency or scalp distribution. However, no study has addressed the mechanism underlying the production of passive P300. In particular, it remains unclear whether the passive P300 shares an identical active P300 generating network architecture when no response is required. This study aims to explore the hierarchical network of passive sensory P300 production using dynamic causal modelling (DCM) for ERP and a novel virtual reality (VR)-based passive oddball paradigm. Moreover, we investigated the causal relationship of this passive P300 network and the changes in connection strength to address the possible functional roles. A classical ERP analysis was performed to verify that the proposed VR-based game can reliably elicit passive P300. The DCM results suggested that the passive and active P300 share the same parietal-frontal neural network for attentional control and, underlying the passive network, the feed-forward modulation is stronger than the feed-back one. The functional role of this forward modulation may indicate the delivery of sensory information, automatic detection of differences, and stimulus-driven attentional processes involved in performing this passive task. To our best knowledge, this is the first study to address the passive P300 network. The results of this study may provide a reference for future clinical studies on addressing the network alternations under pathological states of incommunicative patients. However, caution is required when comparing patients’ analytic results with this study. For example, the task presented here is not applicable to incommunicative patients.

Single-subject-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mild traumatic brain injury

Traumatic brain injury (TBI) is a leading cause of sustained impairment in military and civilian populations. However, mild TBI (mTBI) can be difficult to detect using conventional MRI or CT. Injured brain tissues in mTBI patients generate abnormal slow-waves (1–4 Hz) that can be measured and localized by resting-state magnetoencephalography (MEG). In this study, we develop a voxel-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mTBI on a single-subject basis. A normative database of resting-state MEG source magnitude images (1–4 Hz) from 79 healthy control subjects was established for all brain voxels. The high-resolution MEG source magnitude images were obtained by our recent Fast-VESTAL method. In 84 mTBI patients with persistent post-concussive symptoms (36 from blasts, and 48 from non-blast causes), our method detected abnormalities at the positive detection rates of 84.5%, 86.1%, and 83.3% for the combined (blast-induced plus with non-blast causes), blast, and non-blast mTBI groups, respectively. We found that prefrontal, posterior parietal, inferior temporal, hippocampus, and cerebella areas were particularly vulnerable to head trauma. The result also showed that MEG slow-wave generation in prefrontal areas positively correlated with personality change, trouble concentrating, affective lability, and depression symptoms. Discussion is provided regarding the neuronal mechanisms of MEG slow-wave generation due to deafferentation caused by axonal injury and/or blockages/limitations of cholinergic transmission in TBI. This study provides an effective way for using MEG slow-wave source imaging to localize affected areas and supports MEG as a tool for assisting the diagnosis of mTBI.

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A voxel-based whole-brain MEG slow-wave source imaging method for mild TBI.

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The new approach showed 84.5% positive detection rate in 84 mild TBI patients.

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The new approach detected loci of injury in mild TBI patients on a single-subject basis.

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MEG slow-wave source imaging revealed brain areas vulnerable to mild TBI.

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MEG slow-wave generations correlated with mild TBI symptoms.

PAS-induced potentiation of cortical-evoked activity in the dorsolateral prefrontal cortex

Neuroplasticity and long-term potentiation (LTP) in the dorsolateral prefrontal cortex (DLPFC) are considered important mechanisms in learning and memory, and their disruption may be related to the pathophysiology of several neuropsychiatric disorders. Paired associative stimulation (PAS) is a brain stimulation paradigm that produces enhanced activity in the human motor cortex that may be related to LTP. In a group of 15 healthy participants, we report on the potentiation of cortical-evoked activity in the human DLPFC using the combination of PAS and electroencephalography. In contrast, a PAS control condition did not result in potentiation in another group of nine healthy participants. We also demonstrate that PAS-induced potentiation of cortical-evoked activity is characterized by anatomical specificity that is largely confined to the site of stimulation. Finally, we show that PAS results in potentiation of θ- and γ-activity and θ-phase-γ-amplitude coupling. These neurophysiological indices may be related to working memory, an important function of the DLPFC. To our knowledge, this is the first report of potentiation of cortical-evoked activity in the DLPFC. As this potentiation may be related to LTP, our findings provide a model through which neuroplasticity in health and disease states in the frontal cortex can be studied.

MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL's performance was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL's performance was then examined in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer's problems of signal leaking and distorted source time-courses.

Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPU

This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observations and the underlying probability model. As the EM algorithm is computationally demanding and the analysis faces possible combinatorial explosion of models to be tested, we propose a parallel computing scheme using the GPU to achieve a fast estimation of DCM for ERP. The computation of DCM for ERP is dynamically partitioned and distributed to threads for parallel processing, according to the DCM model complexity and the hardware constraints. The performance efficiency of this hardware-dependent thread arrangement strategy was evaluated using the synthetic data. The experimental data were used to validate the accuracy of the proposed computing scheme and quantify the time saving in practice. The simulation results show that the proposed scheme can accelerate the computation by a factor of 155 for the parallel part. For experimental data, the speedup factor is about 7 per model on average, depending on the model complexity and the data. This GPU-based implementation of DCM for ERP gives qualitatively the same results as the original MATLAB implementation does at the group level analysis. In conclusion, we believe that the proposed GPU-based implementation is very useful for users as a fast screen tool to select the most likely model and may provide implementation guidance for possible future clinical applications such as online diagnosis.

Effect of local anesthesia on trigeminal somatosensory-evoked magnetic fields

For objective neurophysiological evaluation of the function of the trigeminal system, magnetoencephalography- based TSEF (trigeminal somatosensory-evoked field) assessment would be valuable in providing spatial and temporal profiles of cortical responses. However, this necessitates knowledge of how TSEF varies with trigeminal nerve dysfunctions. We introduced a conduction block of the trigeminal nerve using local anesthesia (lidocaine) to temporally mimic nerve dysfunctions, and monitored TSEF changes. Following an electrical stimulation of the lower lip, a magnetic response with peak latency of approximately 20 ms was identified in all participants. Dipole for the peak was estimated on the post-central gyrus in the participant's own magnetic resonance image. After normalization to Montreal Neurological Institute (MNI) space and inter-participant data integration, the summary equivalent current dipole localization among participants remained in the post-central gyrus, suggesting validity of the use of MNI space. Partial anesthesia of the lower lip led to a loss of the waveform characteristics of TSEF for electrical stimulation to the trigeminal nerve. We verified that the 20-ms latency cortical response of TSEF components localized at the primary sensory cortex can serve as a robust neurofunctional marker of experimental trigeminal nerve dysfunction.

Time course of electromagnetic activity associated with detection of rare events

The neural origins of the cortical response to rare sensory events remain poorly understood. Using simultaneous event-related potentials and magnetic resonance imaging, we investigated the anatomical profile of regional activity at various processing stages during performance of auditory and visual variants of an oddball paradigm. The earliest rarity-detection response was found in sensory-specific cortices, rapidly spreading to tertiary association areas, mesial temporal and frontal cortices by 150-200 ms. P3m-related activity was not found in sensory-specific cortices. On the basis of the anatomic distribution of P3m-related activity, this component is likely to reflect more generalized cognitive abilities hosted by association cortical regions.

Face activated neurodynamic cortical networks

Previous neuroimaging studies have shown that complex visual stimuli, such as faces, activate multiple brain regions, yet little is known on the dynamics and complexity of the activated cortical networks during the entire measurable evoked response. In this study, we used simulated and face-evoked empirical MEG data from an oddball study to investigate the feasibility of accurate, efficient, and reliable spatio-temporal tracking of cortical pathways over prolonged time intervals. We applied a data-driven, semiautomated approach to spatio-temporal source localization with no prior assumptions on active cortical regions to explore non-invasively face-processing dynamics and their modulation by task. Simulations demonstrated that the use of multi-start downhill simplex and data-driven selections of time intervals submitted to the Calibrated Start Spatio-Temporal (CSST) algorithm resulted in improved accuracy of the source localization and the estimation of the onset of their activity. Locations and dynamics of the identified sources indicated a distributed cortical network involved in face processing whose complexity was task dependent. This MEG study provided the first non-invasive demonstration, agreeing with intracranial recordings, of an early onset of the activity in the fusiform face gyrus (FFG), and that frontal activation preceded parietal for responses elicited by target faces.

Distinct and shared cerebral activations in processing innocuous versus noxious contact heat revealed by functional magnetic resonance imaging

Whether innocuous heat (IH)-exclusive brain regions exist and whether patterns of cerebral responses to IH and noxious heat (NH) stimulations are similar remain elusive. We hypothesized that distinct and shared cerebral networks were evoked by each type of stimulus. Twelve normal subjects participated in a functional MRI study with rapidly ramped IH (38 degrees C) and NH (44 degrees C) applied to the foot. Group activation maps demonstrated three patterns of cerebral activation: (1) IH-responsive only in the inferior parietal lobule (IPL); (2) NH-responsive only in the primary somatosensory cortex (S1), secondary somatosensory cortex (S2), posterior insular cortex (IC), and premotor area (PMA); and (3) both IH- and NH-responsive in the middle frontal gyrus, inferior frontal gyrus (IFG), anterior IC, cerebellum, superior frontal gyrus, supplementary motor area, thalamus, anterior cingulate cortex (ACC), lentiform nucleus (LN), and midbrain. According to the temporal analysis of regions of interest, the IPL exclusively responded to IH, and the S2, posterior IC, and PMA were exclusively activated by NH throughout the entire period of stimulation. The IFG, thalamus, ACC, and LN responded differently during different phases of IH versus NH stimulation, and the NH-responsive-only S1 responded transiently during the early phase of IH stimulation. BOLD signals in bilateral IPLs were specifically correlated with the ratings of IH sensation, while responses in the contralateral S1 and S2 were correlated with pain intensity. These results suggest that distinct and shared spatial and temporal patterns of cerebral networks are responsible for the perception of IH and NH.

Effects of somatosensory stimulation and attention on human somatosensory cortex: an fMRI study

It is well known that primary and non-primary areas of human somatosensory cortex are involved in the processing of adequate deviant/rare stimuli and omission of frequent stimuli. However, the relative weight and interaction of these variables is poorly known. This functional magnetic resonance imaging (fMRI) study tested the hypothesis that somatosensory stimulus processing and attention especially interact in non-primary somatosensory areas including secondary somatosensory cortex (SII) and insula. To test this hypothesis, responses of somatosensory cortex were mapped during four conditions of an oddball paradigm: DELIVERED COUNT and IGNORE (count or ignore deviant/rare electrical stimuli, respectively); OMITTED COUNT and IGNORE (count or ignore the rare omission of frequent electrical stimuli, respectively). The deviant/rare and frequent electrical stimuli were delivered to median and ulnar nerve, respectively. It was observed that contralateral (left) primary somatosensory responses were not markedly modulated by the mentioned deviant/rare events. Furthermore, contralateral SII and insula responded to all but not OMITTED IGNORE (purely attentive) condition, whereas ipsilateral (right) SII responded to all conditions. Finally, ipsilateral insula responded to the COUNT (attentive) conditions, regardless of the physical presence of the deviant/rare stimuli. The results suggest that in somatosensory modality, bilateral SII and left (contralateral) insula reflect complex integrative processes of stimulus elaboration and attention, whereas right (ipsilateral) insula mainly sub-serves active attention to deviance within a sequence of somatosensory stimuli.

Somatosensory system deficits in schizophrenia revealed by MEG during a median-nerve oddball task

Although impairments related to somatosensory perception are common in schizophrenia, they have rarely been examined in functional imaging studies. In the present study, magnetoencephalography (MEG) was used to identify neural networks that support attention to somatosensory stimuli in healthy adults and abnormalities in these networks in patient with schizophrenia. A median-nerve oddball task was used to probe attention to somatosensory stimuli, and an advanced, high-resolution MEG source-imaging method was applied to assess activity throughout the brain. In nineteen healthy subjects, attention-related activation was seen in a sensorimotor network involving primary somatosensory (S1), secondary somatosensory (S2), primary motor (M1), pre-motor (PMA), and paracentral lobule (PCL) areas. A frontal-parietal-temporal "attention network", containing dorsal- and ventral-lateral prefrontal cortex (DLPFC and VLPFC), orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), superior parietal lobule (SPL), inferior parietal lobule (IPL)/supramarginal gyrus (SMG), and temporal lobe areas, was also activated. Seventeen individuals with schizophrenia showed early attention-related hyperactivations in S1 and M1 but hypo-activation in S1, S2, M1, and PMA at later latency in the sensorimotor network. Within this attention network, hypoactivation was found in SPL, DLPFC, orbitofrontal cortex, and the dorsal aspect of ACC. Hyperactivation was seen in SMG/IPL, frontal pole, and the ventral aspect of ACC in patients. These findings link attention-related somatosensory deficits to dysfunction in both sensorimotor and frontal-parietal-temporal networks in schizophrenia.

Somatosensory discrimination: an intracranial event-related potential study of children with refractory epilepsy

The objective of this study was to determine if a prefrontal somatosensory mismatch response (sMMR) could be recorded in response to deviations in duration of somatosensory stimuli. Intracranial somatosensory event-related potentials were recorded from temporal, parietal, and frontal lobe sites in 12 pediatric patients undergoing evaluation for epilepsy surgery. The stimuli were presented using an oddball paradigm and consisted of short vibratory bursts applied to hand digits 2 and 3. Early sMMRs, consisting of a negative and a positive component, were recorded over the postcentral gyrus and a later one, consisting of only a negative component, was recorded over the left middle frontal gyrus. The presence of an anterior sMMR suggests similar cortical processing to the auditory mismatch negativity (aMMN), with the posterior sMMR reflecting the neuronal processes involved in discriminating between stimuli and this is then followed by the anterior sMMR that may reflect processes involved in switching attention to these changes. The presence of both a prefrontal aMMN and sMMR may reflect activity with a multimodal network.

The functional role of the inferior parietal lobe in the dorsal and ventral stream dichotomy

Current models of the visual pathways have difficulty incorporating the human inferior parietal lobe (IPL) into dorsal or ventral streams. Some recent proposals have attempted to integrate aspects of IPL function that were not hitherto dealt with well, such as differences between the left and right hemisphere and the role of the right IPL in responding to salient environmental events. However, we argue that these models also fail to capture adequately some important findings regarding the functions of the IPL. Here we critically appraise existing proposals regarding the functional architecture of the visual system, with special emphasis on the role of this region, particularly in the right hemisphere. We review evidence that shows the right IPL plays an important role in two different, but broadly complementary, aspects of attention: maintaining attentive control on current task goals as well as responding to salient new information or alerting stimuli in the environment. In our view, findings from functional imaging, electrophysiological and lesion studies are all consistent with the view that this region is part of a system that allows flexible reconfiguration of behaviour between these two alternative modes of operation. Damage to the right IPL leads to deficits in both maintaining attention and also responding to salient events, impairments that contribute to hemineglect, the classical syndrome that follows lesions of this region.

Go-no-go performance in pathological gamblers

Previous neuropsychological studies demonstrated various deficits of impulse control in pathological gamblers (PGs). However, there are limited data available on response-inhibition impairment among PGs. The present study attempted to assess response inhibition in untreated PGs (N=83), in comparison with normal subjects (N=84). Go/no-go and target-detection conditions of a computerized task were used as a measure of response-inhibition ability. A repeated measures analysis of covariance (ANCOVA-RM) was used with response time, variability of response time, and number of false alarms and misses as dependent measures; group (PG and controls) as the between-subjects measure; condition (target detection or go/no-go) and time slice (first and second in each condition) as repeated measures within-subject factors; and educational level as a covariate. Our results showed that PGs were significantly more impaired in both target detection and go/no-go task performance than controls. The PGs had significantly more false alarms and misses than controls, and they were slower and less consistent in their responses.

Changes in cerebral glucose metabolism during early abstinence from chronic methamphetamine abuse

Changes in brain function during the initial weeks of abstinence from chronic methamphetamine abuse may substantially affect clinical outcome, but are not well understood. We used positron emission tomography with [F-18]fluorodeoxyglucose (FDG) to quantify regional cerebral glucose metabolism, an index of brain function, during performance of a vigilance task. A total of 10 methamphetamine-dependent subjects were tested after 5-9 days of abstinence, and after 4 additional weeks of supervised abstinence. A total of 12 healthy control subjects were tested at corresponding times. Global glucose metabolism increased between tests (P=0.01), more in methamphetamine-dependent (10.9%, P=0.02) than control subjects (1.9%, NS). Glucose metabolism did not change in subcortical regions of methamphetamine-dependent subjects, but increased in neocortex, with maximal increase (>20%) in parietal regions. Changes in reaction time and self-reports of negative affect varied more in methamphetamine-dependent than in control subjects, and correlated both with the increase in parietal glucose metabolism, and decrease in relative activity (after scaling to the global mean) in some regions. A robust relationship between change in self-reports of depressive symptoms and relative activity in the ventral striatum may have great relevance to treatment success because of the role of this region in drug abuse-related behaviors. Shifts in cortical-subcortical metabolic balance either reflect new processes that occur during early abstinence, or the unmasking of effects of chronic methamphetamine abuse that are obscured by suppression of cortical glucose metabolism that continues for at least 5-9 days after cessation of methamphetamine self-administration.

Auditory attention—focusing the searchlight on sound

Some fifty years after the first physiological studies of auditory attention, the field is now ripening, with exciting recent insights into the psychophysics, psychology, and neural basis of auditory attention. Current research seeks to unravel the complex interactions of pre-attentive and attentive processing of the acoustic scene, the role of auditory attention in mediating receptive-field plasticity in both auditory spatial and auditory feature processing, the contrasts and parallels between auditory and visual attention pathways and mechanisms, the interplay of bottom-up and top-down attentional mechanisms, the influential role of attention, goals, and expectations in shaping auditory processing, and the orchestration of diverse attentional effects at multiple levels from the cochlea to the cortex.

The Parieto-Frontal Integration Theory (P-FIT) of intelligence: converging neuroimaging evidence

"Is there a biology of intelligence which is characteristic of the normal human nervous system?" Here we review 37 modern neuroimaging studies in an attempt to address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the expression of intelligence and reason. Reviewing studies from functional (i.e., functional magnetic resonance imaging, positron emission tomography) and structural (i.e., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that variations in a distributed network predict individual differences found on intelligence and reasoning tasks. We describe this network as the Parieto-Frontal Integration Theory (P-FIT). The P-FIT model includes, by Brodmann areas (BAs): the dorsolateral prefrontal cortex (BAs 6, 9, 10, 45, 46, 47), the inferior (BAs 39, 40) and superior (BA 7) parietal lobule, the anterior cingulate (BA 32), and regions within the temporal (BAs 21, 37) and occipital (BAs 18, 19) lobes. White matter regions (i.e., arcuate fasciculus) are also implicated. The P-FIT is examined in light of findings from human lesion studies, including missile wounds, frontal lobotomy/leukotomy, temporal lobectomy, and lesions resulting in damage to the language network (e.g., aphasia), as well as findings from imaging research identifying brain regions under significant genetic control. Overall, we conclude that modern neuroimaging techniques are beginning to articulate a biology of intelligence. We propose that the P-FIT provides a parsimonious account for many of the empirical observations, to date, which relate individual differences in intelligence test scores to variations in brain structure and function. Moreover, the model provides a framework for testing new hypotheses in future experimental designs.

Attention and sensory interactions within the occipital cortex in the early blind: an fMRI study

Visual deprivation early in life results in occipital cortical responsiveness across a broad range of perceptual and cognitive tasks. In the reorganized occipital cortex of early blind (EB) individuals, the relative lack of specificity for particular sensory stimuli and tasks suggests that attention effects may play a prominent role in these areas. We wished to establish whether occipital cortical areas in the EB were responsive to stimuli across sensory modalities (auditory, tactile) and whether these areas maintained or altered their activity as a function of selective attention. Using a three-stimulus oddball paradigm and event-related functional magnetic resonance imaging, auditory and tactile tasks presented separately demonstrated that several occipital regions of interest (ROIs) in the EB, but not sighted controls (SCs), responded to targets and task-irrelevant distracter stimuli of both modalities. When auditory and tactile stimuli were presented simultaneously with subjects alternating attention between sensory streams, only the calcarine sulcus continued to respond to stimuli in both modalities. In all other ROIs, responses to auditory targets were as large or larger than those observed in the auditory-alone condition, but responses to tactile targets were attenuated or abolished by the presence of unattended auditory stimuli. Both auditory and somatosensory cortices responded consistently to auditory and tactile targets, respectively. These results reveal mechanisms of orienting and selective attention within the visual cortex of EB individuals and suggest that mechanisms of enhancement and suppression interact asymmetrically on auditory and tactile streams during bimodal sensory presentation.

Generators of the gamma-band activities in response to rare and novel stimuli during the auditory oddball paradigm

In this study, we report the cortical sources of the gamma-band activity emitted during the auditory oddball paradigm using the adaptive beamformer algorithm and non-parametric permutation test and then compare them with those of the P3a and P3b components. The results of the gamma-band current sources revealed that the same gamma-band activities are in process during the rare target and novelty task. In the low (30-55 Hz) gamma-band activity, the common sources were localized in the (inferior) anterior cingulate and adjacent inferior frontal cortex. In the high (65-85 Hz) gamma-band activity, the generator was represented in the superior frontal cortex. On the other hand, the P3a and P3b generators showed widespread distributions including the well-known fronto-parietal network [J. Polich, Theoretical overview of P3a and P3b, in: J. Polish (Ed.), Detection of Change: Event-Related Potential and fMRI Findings, Kluwer Academic Press, Boston, 2003, pp. 83-98]. In conclusion, the same frontal generators of gamma-band activities in the present study may be associated with the functions of attentional control for the binding of consecutive cognitive stages corresponding to earlier P3a and later P3b components, which have distinct source distributions except for some overlaps.

Vector-based spatial–temporal minimum L1-norm solution for MEG

Minimum L1-norm solutions have been used by many investigators to analyze MEG responses because they provide high spatial resolution images. However, conventional minimum L1-norm approaches suffer from instability in spatial construction, and poor smoothness of the reconstructed source time-courses. Activity commonly "jumps" from one grid point to (usually) the neighboring grid points. Equivalently, the time-course of one specific grid point can show substantial "spiky-looking" discontinuity. In the present study, we present a new vector-based spatial-temporal analysis using a L1-minimum-norm (VESTAL). This approach is based on a principle of MEG physics: the magnetic waveforms in sensor-space are linear functions of the source time-courses in the imaging-space. Our computer simulations showed that VESTAL provides good reconstruction of the source amplitude and orientation, with high stability and resolution in both the spatial and temporal domains. "Spiky-looking" discontinuity was not observed in the source time-courses. Importantly, the simulations also showed that VESTAL can resolve sources that are 100% correlated. We then examined the performance of VESTAL in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguishes sources very spatially close to each other, including individual primary somatosensory areas (BA 1, 2, 3b), primary motor area (BA 4), and other regions in the somatosensory system (e.g., BA 5, 7, SII, SMA, and temporal-parietal junction) with high temporal stability and resolution. VESTAL's potential for obtaining information on source extent was also examined.