Cortical Activation Patterns Research Articles

Gabaergic Interneurons in Early Brain Development: Conducting and Orchestrated by Cortical Network Activity.

Throughout early phases of brain development, the two main neural signaling mechanisms—excitation and inhibition—are dynamically sculpted in the neocortex to establish primary functions. Despite its relatively late formation and persistent developmental changes, the GABAergic system promotes the ordered shaping of neuronal circuits at the structural and functional levels. Within this frame, interneurons participate first in spontaneous and later in sensory-evoked activity patterns that precede cortical functions of the mature brain. Upon their subcortical generation, interneurons in the embryonic brain must first orderly migrate to and settle in respective target layers before they can actively engage in cortical network activity. During this process, changes at the molecular and synaptic level of interneurons allow not only their coordinated formation but also the pruning of connections as well as excitatory and inhibitory synapses. At the postsynaptic site, the shift of GABAergic signaling from an excitatory towards an inhibitory response is required to enable synchronization within cortical networks. Concomitantly, the progressive specification of different interneuron subtypes endows the neocortex with distinct local cortical circuits and region-specific modulation of neuronal firing. Finally, the apoptotic process further refines neuronal populations by constantly maintaining a controlled ratio of inhibitory and excitatory neurons. Interestingly, many of these fundamental and complex processes are influenced—if not directly controlled—by electrical activity. Interneurons on the subcellular, cellular, and network level are affected by high frequency patterns, such as spindle burst and gamma oscillations in rodents and delta brushes in humans. Conversely, the maturation of interneuron structure and function on each of these scales feeds back and contributes to the generation of cortical activity patterns that are essential for the proper peri- and postnatal development. Overall, a more precise description of the conducting role of interneurons in terms of how they contribute to specific activity patterns—as well as how specific activity patterns impinge on their maturation as orchestra members—will lead to a better understanding of the physiological and pathophysiological development and function of the nervous system.

The Computational and Neural Substrates of Ambiguity Avoidance in Anxiety.

Theoretical accounts have linked anxiety to intolerance of ambiguity. However, this relationship has not been well operationalized empirically. Here, we used computational and neuro-imaging methods to characterize anxiety-related differences in aversive decision-making under ambiguity and associated patterns of cortical activity. Adult human participants chose between two urns on each trial. The ratio of tokens (‘O’s and ‘X’s) in each urn determined probability of electrical stimulation receipt. A number above each urn indicated the magnitude of stimulation that would be received if a shock was delivered. On ambiguous trials, one of the two urns had tokens occluded. By varying the number of tokens occluded, we manipulated the extent of missing information. At higher levels of missing information, there is greater second order uncertainty, i.e., more uncertainty as to the probability of pulling a given type of token from the urn. Adult human participants demonstrated avoidance of ambiguous options which increased with level of missing information. Extent of ‘information-level dependent’ ambiguity aversion was significantly positively correlated with trait anxiety. Activity in both the dorsal anterior cingulate cortex and inferior frontal sulcus during the decision-making period increased as a function of missing information. Greater engagement of these regions, on high missing information trials, was observed when participants went on to select the ambiguous option; this was especially apparent in high trait anxious individuals. These findings are consistent with individuals vulnerable to anxiety requiring greater activation of frontal regions supporting rational decision-making to overcome a predisposition to engage in ambiguity avoidance at high levels of missing information.

The impact of accuracy on functional neural correlates of the useful field of view (UFOV) task

AbstractBackgroundRapid declines in processing speed performance occur in aging and serve as a critical marker of cognitive abilities. Studies suggest that Useful Field of View (UFOV) training may ameliorate cognitive decline. The ACTIVE trial, consisting of over 2,800 participants, found a 29% reduction in ADRD risk 10 years following intervention. Recent clinical trials aimed at slowing cognitive decline in AD have focused on UFOV‐based interventions. Despite its efficacy, little is known about its neural correlates. The current study investigated blood‐oxygen level dependent (BOLD) activation patterns of the UFOV task.Method233 older adults completed the UFOV task while undergoing task‐based fMRI. The UFOV task requires participants to identify a central target, as well as a peripheral target amongst distractors, presented for a brief period of time. First‐level contrasts modeled hemodynamic response, while second‐level analyses assessed unique BOLD activation associated with encoding and recall components of the task. Age, education, sex and scanner were included as covariates. Significant clusters were defined as >10 voxels, and all clusters were corrected at a false discovery rate (FDR) of p<0.05.ResultPrevious data have shown widespread bilateral whole‐brain activation associated with the encoding component, whereas discrete activation patterns were related to the recall component of the task. Additionally, numerous shared brain regions were critical to both the encoding and recall components of the UFOV task. We further investigated cortical activation patterns associated with age‐related differences in UFOV performance. Variability in performance was related to widespread patterns of activation during the encoding component of the UFOV task, namely the superior parietal lobule, insula, hippocampus and DLPFC. Assessing UFOV performance variability within recall, no significant clusters survived FDR correction. Furthermore, the inferior parietal lobule, cerebellum, and inferior frontal gyrus were critical in both encoding and recall in UFOV performance.ConclusionThe present study elucidates pivotal regions associated with UFOV task performance. Notably, we found that variability in UFOV performance is directly associated with neural activation during the presentation/apprehension of the stimuli, but not during recall. These findings suggest that variation in neural activation during speeded attentional processing is central to age‐related UFOV performance differences, and interventions targeting these neural processes may be of benefit.

Abnormal Cortical Activation Patterns Among Chinese-Speaking Schizophrenia Patients During Category and Letter Verbal Fluency Tasks Revealed by Multi-Channel Functional Near-Infrared Spectroscopy.

Background: Functional near-infrared spectroscopy (fNIRS) has many advantages over other neuroimaging modalities for routine measurement of task-dependent cortical activation, but most fNIRS studies of schizophrenia have used letter fluency tasks (LFTs). Further, performances on category fluency tasks (CFTs) and LFTs may be distinct in Chinese patients due to the unique semantic features of Chinese written characters. To identify unique disease biomarkers measurable by fNIRS in Chinese schizophrenia patients, this study compared cortical oxygenated hemoglobin changes ([oxy-Hb]) during a Chinese LFT and CFT between patients and healthy controls.Methods: Inpatients of the Second Affiliated Hospital of Xinxiang Medical University were recruited from Match 2020 to July 2021. The Positive and Negative Symptom Scale (PANSS) was used to evaluate psychiatric symptoms. Dynamic changes in [oxy-Hb], an indicator of neural activity, were measured during CFT and LFT performance by 52-channel fNIRS.Results: Forty-seven schizophrenia inpatients and 29 healthy controls completed all tests. Schizophrenia patients showed significant cortical activation at 15 channels covering the left hemisphere and 17 channels over the right hemisphere during the CFT. During the LFT, activity was significantly increased at only six channels, all over the left hemisphere (FDR P < 0.05). In healthy controls, significant [oxy-Hb] increases were found at 24 channels over the left hemisphere and 19 channels over the right hemisphere during CFT. While during the LFT, the significant increases were found at 7 channels all over the left hemisphere (FDR P < 0.05). When years of education was included as a covariate, the schizophrenia group demonstrated no significant hypoactivation relative to healthy controls at any channel after FDR correction (FDR P < 0.05) during CFT while demonstrated significant hypoactivation at channel 11 during LFT (FDR P < 0.05). There were no significant associations between PANSS scores and [oxy-Hb] changes after FDR correction (FDR P < 0.05).Conclusions: Left lateralization during CFT was reduced among schizophrenia patients and may be related to the semantic deficit. The Chinese-CFT could be a more sensitive indicator of frontal-temporal dysfunction in schizophrenia.

Human intracranial recordings reveal distinct cortical activity patterns during invasive and non-invasive vagus nerve stimulation

Vagus nerve stimulation (VNS) is being used increasingly to treat a wide array of diseases and disorders. This growth is driven in part by the putative ability to stimulate the nerve non-invasively. Despite decades of use and a rapidly expanding application space, we lack a complete understanding of the acute effects of VNS on human cortical neurophysiology. Here, we investigated cortical responses to sub-perceptual threshold cervical implanted (iVNS) and transcutaneous auricular (taVNS) vagus nerve stimulation using intracranial neurophysiological recordings in human epilepsy patients. To understand the areas that are modulated by VNS and how they differ depending on invasiveness and stimulation parameters, we compared VNS-evoked neural activity across a range of stimulation modalities, frequencies, and amplitudes. Using comparable stimulation parameters, both iVNS and taVNS caused subtle changes in low-frequency power across broad cortical networks, which were not the same across modalities and were highly variable across participants. However, within at least some individuals, it may be possible to elicit similar responses across modalities using distinct sets of stimulation parameters. These results demonstrate that both invasive and non-invasive VNS cause evoked changes in activity across a set of highly distributed cortical networks that are relevant to a diverse array of clinical, rehabilitative, and enhancement applications.

Effect of MRgFUS treatment on cortical activity in Parkinson's disease: a fNIRS study

n this paper, a new combined approach, based on Magnetic Resonance-guided Focused Ultrasound Surgery (MRgFUS) technique and functional Near Infrared Spectroscopy (fNIRS), was applied for treatment and monitoring of patients affected by bilateral Parkinson’s disease (PD). On one side, MRgFUS enables non-invasive thalamotomy by combining FUS for tissue ablation and MR for targeting and monitoring. On the other side, fNIRS allows to monitor, non-invasively and without strict motion restriction even in a daily life environment, cortical neural activity related dynamics of both oxygenated and deoxygenated haemoglobin (HbO and HbR, respectively). In particular, the changes of cortical activation pattern in PD patients, with respect to age matched healthy control subjects, were analysed, while performing left and right hand finger tapping (LFT and RFT, respectively), before MRgFUS treatment, and at two different time intervals after the treatment. By comparison with the pre-treatment session, significant activations were predominantly observed one week after the treatment, with patterns recalling those of control group, and partially lost one month later, likely because of the neurodegenerative nature of PD. In addition, activations were more marked for LFT task, being the treatment performed on the right hemisphere. These results appear promising in view of the application of fNIRS for neurorehabilitation, especially in those clinical settings where traditional neuroimaging techniques cannot be applied.

Somatosensory perturbations influence cortical activity associated with single-limb balance performance.

To determine the association between cortical activity and postural control performance changes with differing somatosensory perturbations. Healthy individuals (n = 15) performed a single-limb balance task under four conditions: baseline, unstable surface (foam), transcutaneous electrical nerve stimulation (TENS) applied to the stance-limb knee, and combined foam + TENS. Cortical activity was recorded with electroencephalography (EEG) and postural sway via triaxial force plate. EEG signals were decomposed, localized, and clustered to generate power spectral density in theta (4-7Hz) and alpha-2 (10-12Hz) frequency bands in anatomical clusters. Postural sway signals were analyzed with center of pressure (COP) sway metrics (e.g., area, distance, velocity). Foam increased theta power in the frontal and central clusters (d = 0.77 to 1.16), decreased alpha-2 power in bilateral motor, right parietal, and occipital clusters (d = - 0.89 to - 2.35) and increased sway area, distance, and velocity (d = 1.09-2.57) relative to baseline. Conversely, TENS decreased central theta power (d = - 0.60), but increased bilateral motor, left parietal, and occipital alpha-2 power (d = 0.51-1.40), with similar to baseline balance performance. In combination, foam + TENS attenuated sway velocity detriments and cortical activity caused by the foam condition alone. There were weak and moderate associations between percent increased central theta and occipital activity and increased sway velocity. Somatosensory perturbations changed patterns of cortical activity during a single-limb balance task in a manner suggestive of sensory re-weighting to pertinent sensory feedback. Across conditions decreased cortical activity in pre-motor and visual regions were associated with reduced sway velocity.

The Differences Between Motor Attempt and Motor Imagery in Brain-Computer Interface Accuracy and Event-Related Desynchronization of Patients With Hemiplegia.

Background: Motor attempt and motor imagery (MI) are two common motor tasks used in brain-computer interface (BCI). They are widely researched for motor rehabilitation in patients with hemiplegia. The differences between the motor attempt (MA) and MI tasks of patients with hemiplegia can be used to promote BCI application. This study aimed to explore the accuracy of BCI and event-related desynchronization (ERD) between the two tasks.Materials and Methods: We recruited 13 patients with stroke and 3 patients with traumatic brain injury, to perform MA and MI tasks in a self-control design. The BCI accuracies from the bilateral, ipsilesional, and contralesional hemispheres were analyzed and compared between different tasks. The cortical activation patterns were evaluated with ERD and laterality index (LI).Results: The study showed that the BCI accuracies of MA were significantly (p < 0.05) higher than MI in the bilateral, ipsilesional, and contralesional hemispheres in the alpha-beta (8–30 Hz) frequency bands. There was no significant difference in ERD and LI between the MA and MI tasks in the 8–30 Hz frequency bands. However, in the MA task, there was a negative correlation between the ERD values in the channel CP1 and ipsilesional hemispheric BCI accuracies (r = −0.552, p = 0.041, n = 14) and a negative correlation between the ERD values in channel CP2 and bilateral hemispheric BCI accuracies (r = −0.543, p = 0.045, n = 14). While in the MI task, there were negative correlations between the ERD values in channel C4 and bilateral hemispheric BCI accuracies (r = −0.582, p = 0.029, n = 14) as well as the contralesional hemispheric BCI accuracies (r = −0.657, p = 0.011, n = 14). As for motor dysfunction, there was a significant positive correlation between the ipsilesional BCI accuracies and FMA scores of the hand part in 8–13 Hz (r = 0.565, p = 0.035, n = 14) in the MA task and a significant positive correlation between the ipsilesional BCI accuracies and FMA scores of the hand part in 13–30 Hz (r = 0.558, p = 0.038, n = 14) in the MI task.Conclusion: The MA task may achieve better BCI accuracy but have similar cortical activations with the MI task. Cortical activation (ERD) may influence the BCI accuracy, which should be carefully considered in the BCI motor rehabilitation of patients with hemiplegia.

Energy-Based Hierarchical Clustering of Cortical Slow Waves in Multi-Electrode Recordings.

The recent development of novel multi-electrode recording technologies has revealed the existence of traveling patterns of cortical activity in many species and under different states of awareness. Among these, slow activation waves occurring under sleep and anesthesia have been widely investigated as they provide unique insights into network features such as excitability, connectivity, structure, and dynamics of the cerebral cortex. Such characterization is usually based on clustering methods which are constrained by a priori assumptions as to the number of clusters to be used or rely on wave-by-wave pattern reconstruction. Here, we introduce a new computational tool based on modal analysis of fluid flows which is robustly applied to multivariate electrophysiological data from cortical networks, namely the Energy-based Hierarchical Waves Clustering method (EHWC). EHWC is composed of three main steps: (1) detecting the occurrence of global waves; (2) reducing the data dimensionality via singular value decomposition; (3) clustering hierarchically the singled-out waves. The analysis does not require the single-channel contribution to the waves, which is a typical bottleneck in this kind of analysis due to the unavoidable intrinsic variability of locally recorded activity. For testing and validation, here we used in vivo extracellular recordings from mice cortex under three different levels of anesthesia. As a result, we found slow waves with an increasing number of propagation modes as the anesthesia level decreases, giving an estimate of the increasing complexity of network dynamics. This and other wave's features replicate and extend the findings from previous literature, paving the way to extend the same approach to non-invasive electrophysiological recordings like EEG and fMRI used clinically for the characterization of brain dynamics and clinical stratification in brain lesions.

Cortical activation during gait adaptability in people with Parkinson’s disease

BackgroundPeople with Parkinson’s disease (PD) have difficulties adapting their gait. While underlying neural mechanisms involving the prefrontal cortex (PFC) have been studied across various complex walking tasks, less is known about the premotor cortex (PMC) and supplementary motor area (SMA), key cortical regions for motor planning. This study compared frontal cortical regions activation patterns using functional near-infrared spectroscopy (fNIRS), between people with PD and healthy controls (HC) during gait adaptability tasks. MethodsForty-nine people with PD (mean (SD) age: 69.5 (7.9) years) and 21 HC (69.0 (5.9) years) completed a simple walk and three randomly presented gait adaptability tasks: (i) stepping on targets, (ii) avoiding obstacles and (iii) negotiating both targets and obstacles. Cortical activity in the dorsolateral PFC (DLPFC), SMA and PMC were recorded using fNIRS. Step length, velocity and accuracy and cortical activity were contrasted between the groups and walking conditions. ResultsCompared with the HC, the PD group exhibited greater PMC activation and walked significantly slower and took shorter steps in all conditions. A statistically significant group by condition interaction indicated an increase in DLPFC cortical activation in the HC participants when undertaking the obstacle avoidance task compared with the simple walk but no increase in cortical activation in the PD group when undergoing this more challenging gait task. ConclusionsOur findings suggest people with PD have little or no DLPFC, SMA and PMC capacity beyond what they need for simple walking and in consequence need to slow their gait velocity to meet the demands of target stepping and obstacle avoidance tasks. Such behavioral and neural patterns appear consistent with concepts of compensatory over-activation and capacity limitation.

Extremely fast pRF mapping for real-time applications

Population receptive field (pRF) mapping is a popular tool in computational neuroimaging that allows for the investigation of receptive field properties, their topography and interrelations in health and disease. Furthermore, the possibility to invert population receptive fields provides a decoding model for constructing stimuli from observed cortical activation patterns. This has been suggested to pave the road towards pRF-based brain-computer interface (BCI) communication systems, which would be able to directly decode internally visualized letters from topographically organized brain activity. A major stumbling block for such an application is, however, that the pRF mapping procedure is computationally heavy and time consuming. To address this, we propose a novel and fast pRF mapping procedure that is suitable for real-time applications. The method is built upon hashed-Gaussian encoding of the stimulus, which tremendously reduces computational resources. After the stimulus is encoded, mapping can be performed using either ridge regression for fast offline analyses or gradient descent for real-time applications. We validate our model-agnostic approach in silico, as well as on empirical fMRI data obtained from 3T and 7T MRI scanners. Our approach is capable of estimating receptive fields and their parameters for millions of voxels in mere seconds. This method thus facilitates real-time applications of population receptive field mapping.

Precise Topology of Adjacent Domain-General and Sensory-Biased Regions in the Human Brain.

Recent functional MRI studies identified sensory-biased regions across much of the association cortices and cerebellum. However, their anatomical relationship to multiple-demand (MD) regions, characterized as domain-general due to their coactivation during multiple cognitive demands, remains unclear. For a better anatomical delineation, we used multimodal MRI techniques of the Human Connectome Project to scan subjects performing visual and auditory versions of a working memory (WM) task. The contrast between hard and easy WM showed strong domain generality, with essentially identical patterns of cortical, subcortical, and cerebellar MD activity for visual and auditory materials. In contrast, modality preferences were shown by contrasting easy WM with baseline; most MD regions showed visual preference while immediately adjacent to cortical MD regions, there were interleaved regions of both visual and auditory preference. The results may exemplify a general motif whereby domain-specific regions feed information into and out of an adjacent, integrative MD core.

Narrative event segmentation in the cortical reservoir.

Recent research has revealed that during continuous perception of movies or stories, humans display cortical activity patterns that reveal hierarchical segmentation of event structure. Thus, sensory areas like auditory cortex display high frequency segmentation related to the stimulus, while semantic areas like posterior middle cortex display a lower frequency segmentation related to transitions between events. These hierarchical levels of segmentation are associated with different time constants for processing. Likewise, when two groups of participants heard the same sentence in a narrative, preceded by different contexts, neural responses for the groups were initially different and then gradually aligned. The time constant for alignment followed the segmentation hierarchy: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. These hierarchical segmentation phenomena can be considered in the context of processing related to comprehension. In a recently described model of discourse comprehension word meanings are modeled by a language model pre-trained on a billion word corpus. During discourse comprehension, word meanings are continuously integrated in a recurrent cortical network. The model demonstrates novel discourse and inference processing, in part because of two fundamental characteristics: real-world event semantics are represented in the word embeddings, and these are integrated in a reservoir network which has an inherent gradient of functional time constants due to the recurrent connections. Here we demonstrate how this model displays hierarchical narrative event segmentation properties beyond the embeddings alone, or their linear integration. The reservoir produces activation patterns that are segmented by a hidden Markov model (HMM) in a manner that is comparable to that of humans. Context construction displays a continuum of time constants across reservoir neuron subsets, while context forgetting has a fixed time constant across these subsets. Importantly, virtual areas formed by subgroups of reservoir neurons with faster time constants segmented with shorter events, while those with longer time constants preferred longer events. This neurocomputational recurrent neural network simulates narrative event processing as revealed by the fMRI event segmentation algorithm provides a novel explanation of the asymmetry in narrative forgetting and construction. The model extends the characterization of online integration processes in discourse to more extended narrative, and demonstrates how reservoir computing provides a useful model of cortical processing of narrative structure.

Clinical and research vestibular neuro-imaging

Current knowledge of multisensory vestibular structures and their functions in the human cortex will be presented as revealed from brain activation studies of the last two decades with PET and MRI. These tools confirmed that humans have several separate cortical areas that tracer and electrophysiological studies in animals, especially in monkeys, had identified earlier. First, the pathways from the vestibular nuclei in the brainstem to vestibular cortical areas are described in normals, followed by the typical cortical activation pattern of unilateral vestibular stimulation.

Local neuronal relational structures underlying the contents of human conscious experience.

While most theories of consciousness posit some kind of dependence on global network activities, I consider here an alternative, localist perspective—in which localized cortical regions each underlie the emergence of a unique category of conscious experience. Under this perspective, the large-scale activation often found in the cortex is a consequence of the complexity of typical conscious experiences rather than an obligatory condition for the emergence of conscious awareness—which can flexibly shift, depending on the richness of its contents, from local to more global activation patterns. This perspective fits a massive body of human imaging, recordings, lesions and stimulation data but opens a fundamental problem: how can the information, defining each content, be derived locally in each cortical region. Here, I will discuss a solution echoing pioneering structuralist ideas in which the content of a conscious experience is defined by its relationship to all other contents within an experiential category. In neuronal terms, this relationship structure between contents is embodied by the local geometry of similarity distances between cortical activation patterns generated during each conscious experience, likely mediated via networks of local neuronal connections. Thus, in order for any conscious experience to appear in an individual’s mind, two central conditions must be met. First, a specific configural pattern (“bar-code”) of neuronal activity must appear within a local relational geometry, i.e. a cortical area. Second, the individual neurons underlying the activated pattern must be bound into a unified functional ensemble through a burst of recurrent neuronal firing: local “ignitions”.

Brain activations associated with anticipation and delivery of monetary reward: A systematic review and meta-analysis of fMRI studies.

While multiple studies have examined the brain functional correlates of reward, meta-analyses have either focused on studies using the monetary incentive delay (MID) task, or have adopted a broad strategy, combining data from studies using both monetary and non-monetary reward, as probed using a wide range of tasks. To meta-analyze fMRI studies that used monetary reward and in which there was a definable cue-reward contingency. Studies were limited to those using monetary reward in order to avoid potential heterogeneity from use of other rewards, especially social rewards. Studies using gambling or delay discounting tasks were excluded on the grounds that reward anticipation is not easily quantifiable. English-language fMRI studies (i) that reported fMRI findings on healthy adults; (ii) that used monetary reward; and (iii) in which a cue that was predictive of reward was compared to a no win (or lesser win) condition. Only voxel-based studies were included; those where brain coverage was incomplete were excluded. Ovid, Medline and PsycInfo, from 2000 to 2020, plus checking of review articles and meta-analyses. Data were pooled using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI). Heterogeneity among studies was examined using the I2 statistic. Publication bias was examined using funnel plots and statistical examination of asymmetries. Moderator variables including whether the task was pre-learnt, sex distribution, amount of money won and width of smoothing kernel were examined. Pooled data from 45 studies of reward anticipation revealed activations in the ventral striatum, the middle cingulate cortex/supplementary motor area and the insula. Pooled data from 28 studies of reward delivery again revealed ventral striatal activation, plus cortical activations in the anterior and posterior cingulate cortex. There was relatively little evidence of publication bias. Among moderating variables, only whether the task was pre-learnt exerted an influence. According to this meta-analysis monetary reward anticipation and delivery both activate the ventral but not the dorsal striatum, and are associated with different patterns of cortical activation.

Theta-gamma coupling during REM sleep depends on breathing rate.

Temporal coupling between theta and gamma oscillations is a hallmark activity pattern of several cortical networks and becomes especially prominent during REM sleep. In a parallel approach, nasal breathing has been recently shown to generate phase-entrained network oscillations which also modulate gamma. Both slow rhythms (theta and respiration-entrained oscillations) have been suggested to aid large-scale integration but they differ in frequency, display low coherence, and modulate different gamma sub-bands. Respiration and theta are therefore believed to be largely independent. In the present work, however, we report an unexpected but robust relation between theta-gamma coupling and respiration in mice. Interestingly, this relation takes place not through the phase of individual respiration cycles, but through respiration rate: the strength of theta-gamma coupling exhibits an inverted V-shaped dependence on breathing rate, leading to maximal coupling at breathing frequencies of 4-6 Hz. Noteworthy, when subdividing sleep epochs into phasic and tonic REM patterns, we find that breathing differentially relates to theta-gamma coupling in each state, providing new evidence for their physiological distinctiveness. Altogether, our results reveal that breathing correlates with brain activity not only through phase-entrainment but also through rate-dependent relations with theta-gamma coupling. Thus, the link between respiration and other patterns of cortical network activity is more complex than previously assumed.

Representation learning of resting state fMRI with variational autoencoder

Resting state functional magnetic resonance imaging (rsfMRI) data exhibits complex but structured patterns. However, the underlying origins are unclear and entangled in rsfMRI data. Here we establish a variational auto-encoder, as a generative model trainable with unsupervised learning, to disentangle the unknown sources of rsfMRI activity. After being trained with large data from the Human Connectome Project, the model has learned to represent and generate patterns of cortical activity and connectivity using latent variables. The latent representation and its trajectory represent the spatiotemporal characteristics of rsfMRI activity. The latent variables reflect the principal gradients of the latent trajectory and drive activity changes in cortical networks. Representational geometry captured as covariance or correlation between latent variables, rather than cortical connectivity, can be used as a more reliable feature to accurately identify subjects from a large group, even if only a short period of data is available in each subject. Our results demonstrate that VAE is a valuable addition to existing tools, particularly suited for unsupervised representation learning of resting state fMRI activity.

Movement kinematics and cortical activation in children with and without autism spectrum disorder during sway synchrony tasks: an fNIRS study

Children with Autism Spectrum Disorder (ASD) have difficulties with socially embedded movements such as imitation and interpersonal synchrony (IPS); however, related movement characteristics and underlying neural mechanisms are not well understood. This study compared the movement characteristics and cortical activation patterns of children with and without ASD during a whole-body, sway synchrony task when different levels of social information were provided. Thirty children with and without ASD (mean age: 12.6 years, SE: 0.6 years) participated. Movement kinematics and fNIRS-based cortical activation were recorded when the child observed an adult tester sway side to side, when they swayed solo, or when they swayed face to face with the tester with or without fingertips touching (i.e., IPS). Children with ASD showed reduced synchrony and smaller sway amplitude compared to typically developing children without ASD. They showed reduced cortical activation over the inferior frontal gyrus and superior temporal sulcus during IPS and did not show significant increase in cortical activation when more social information was provided. The cortical activation findings were significantly associated with IPS behaviors and social communication performance. The ASD-related neurobiomarkers identified in our study could be used as objective measures to evaluate intervention effects in children with ASD.

Cellular-resolution monitoring of ischemic stroke pathologies in the rat cortex.

Stroke is a leading cause of disability in the Western world. Current post-stroke rehabilitation treatments are only effective in approximately half of the patients. Therefore, there is a pressing clinical need for developing new rehabilitation approaches for enhancing the recovery process, which requires the use of appropriate animal models. Here, we demonstrate the use of nonlinear microscopy of calcium sensors in the rat brain to study the effects of ischemic stroke injury on cortical activity patterns. We longitudinally recorded from thousands of neurons labeled with a genetically-encoded calcium indicator before and after an ischemic stroke injury in the primary motor cortex. We show that this injury has an effect on the activity patterns of neurons not only in the motor and somatosensory cortices, but also in the more distant visual cortex, and that these changes include modified firing rates and kinetics of neuronal activity patterns in response to a sensory stimulus. Changes in neuronal population activity provided animal-specific, circuit-level information on the post-stroke cortical reorganization process, which may be essential for evaluating the efficacy of new approaches for enhancing the recovery process.