Cortical Signals Research Articles

Motivation-related influences on fNIRS signals during walking exercise: a permutation entropy approach.

Cortical activity is typically indexed by analyzing functional near-infrared spectroscopy (fNIRS) signals in terms of the mean (e.g., mean oxygenated hemoglobin; HbO). Entropy approaches have been proposed as useful complementary methods for analyzing fNIRS signals. Entropy methods consider the regularity of a time series, and in doing so, may provide additional insights into the underlying dynamics of brain activity. Recent research using fNIRS found that non-disabled adults exhibit widespread increases in cortical activity and walk faster when under "extra motivation" conditions (e.g., verbal encouragement, lap timer) compared to trials without such motivators ("standard motivation"). This ancillary analysis of that study aimed to assess the extent to which fNIRS permutation entropy (PE) was affected by motivational conditions and explained variance in self-reported motivation. No regional PE differences were found between different motivational conditions. However, a greater difference in PE between motivational conditions (higher in standard, lower in extra motivation) in the anterior prefrontal cortex (aPFC) was associated with greater self-determined motivation. PE was also higher (less regular) in the primary sensorimotor cortex lower limb area compared to all other cortical areas analyzed, except the dorsal premotor cortex, regardless of motivational condition. This study provides early evidence to suggest that while different motivational environments during walking activity influence the magnitude of fNIRS signals, they may not influence the regularity of cortical signals. However, the magnitude of PE difference between motivational conditions was related to self-determined motivation in the aPFC, and this is an area warranting further investigation.

Contribution of extracerebral tracer retention and partial volume effects to sex differences in Flortaucipir-PET signal

Clinically normal females exhibit higher 18F-flortaucipir (FTP)-PET signal than males across the cortex. However, these sex differences may be explained by neuroimaging idiosyncrasies such as off-target extracerebral tracer retention or partial volume effects (PVEs). 343 clinically normal participants (female = 58%; mean[SD]=73.8[8.5] years) and 55 patients with mild cognitive impairment (female = 38%; mean[SD] = 76.9[7.3] years) underwent cross-sectional FTP-PET. We parcellated extracerebral FreeSurfer areas based on proximity to cortical ROIs. Sex differences in cortical tau were then estimated after accounting for local extracerebral retention. We simulated PVE by convolving group-level standardized uptake value ratio means in each ROI with 6 mm Gaussian kernels and compared the sexes across ROIs post-smoothing. Widespread sex differences in extracerebral retention were observed. Although attenuating sex differences in cortical tau-PET signal, covarying for extracerebral retention did not impact the largest sex differences in tau-PET signal. Differences in PVE were observed in both female and male directions with no clear sex-specific bias. Our findings suggest that sex differences in FTP are not solely attributed to off-target extracerebral retention or PVE, consistent with the notion that sex differences in medial temporal and neocortical tau are biologically driven. Future work should investigate sex differences in regional cerebral blood flow kinetics and longitudinal tau-PET.

Express Visuomotor Responses Reflect Knowledge of Both Target Locations and Contextual Rules during Reaches of Different Amplitudes.

When humans reach to visual targets, extremely rapid (∼90 ms) target-directed responses can be observed in task-relevant proximal muscles. Such express visuomotor responses are inflexibly locked in time and space to the target and have been proposed to reflect rapid visuomotor transformations conveyed subcortically via the tecto-reticulo-spinal pathway. Previously, we showed that express visuomotor responses are sensitive to explicit cue-driven information about the target, suggesting that the express pathway can be modulated by cortical signals affording contextual prestimulus expectations. Here, we show that the express visuomotor system incorporates information about the physical hand-to-target distance and contextual rules during visuospatial tasks requiring different movement amplitudes. In one experiment, we recorded the activity from two shoulder muscles as 14 participants (6 females) reached toward targets that appeared at different distances from the reaching hand. Increasing the reaching distance facilitated the generation of frequent and large express visuomotor responses. This suggests that both the direction and amplitude of veridical hand-to-target reaches are encoded along the putative subcortical express pathway. In a second experiment, we modulated the movement amplitude by asking 12 participants (4 females) to deliberately undershoot, overshoot, or stop (control) at the target. The overshoot and undershoot tasks impaired the generation of large and frequent express visuomotor responses, consistent with the inability of the express pathway to generate responses directed toward nonveridical targets as in the anti-reach task. Our findings appear to reflect strategic, cortically driven modulation of the express visuomotor circuit to facilitate rapid and effective response initiation during target-directed actions.SIGNIFICANCE STATEMENT Express (∼90 ms) arm muscle responses that are consistently tuned toward the location of visual stimuli suggest a subcortical contribution to target-directed visuomotor behavior in humans, potentially via the tecto-reticulo-spinal pathway. Here, we show that express muscle responses are modulated appropriately to reach targets at different distances, but generally suppressed when the task required nonveridical responses to overshoot/undershoot the real target. This suggests that the tecto-reticulo-spinal pathway can be exploited strategically by the cerebral cortex to facilitate rapid initiation of effective responses during a visuospatial task.

An E-cadherin-actin clutch translates the mechanical force of cortical flow for cell-cell contact to inhibit epithelial cell locomotion.

Adherens junctions (AJs) allow cell contact to inhibit epithelial migration yetalso permit epithelia to move as coherent sheets. How, then, do cells identify which contacts will inhibit locomotion? Here, we show that in human epithelial cells this arises from the orientation of cortical flows at AJs. When the leader cells from different migrating sheets make head-on contact with one another, they assemble AJs that couple together oppositely directed cortical flows. This applies a tensile signal to the actin-binding domain (ABD) of α-catenin, which provides a clutch to promote lateral adhesion growth and inhibit the lamellipodial activity necessary for migration. In contrast, AJs found between leader cells in the same migrating sheet have cortical flows aligned in the same direction, and no such mechanical inhibition takes place. Therefore, α-catenin mechanosensitivity in the clutch between E-cadherin and cortical F-actin allows cells to interpret the direction of motion via cortical flows and signal for contact to inhibit locomotion.

Synaptic network structure shapes cortically evoked spatio-temporal responses of STN and GPe neurons in a computational model.

The basal ganglia (BG) are involved in motor control and play an essential role in movement disorders such as hemiballismus, dystonia, and Parkinson's disease. Neurons in the motor part of the BG respond to passive movement or stimulation of different body parts and to stimulation of corresponding cortical regions. Experimental evidence suggests that the BG are organized somatotopically, i.e., specific areas of the body are associated with specific regions in the BG nuclei. Signals related to the same body part that propagate along different pathways converge onto the same BG neurons, leading to characteristic shapes of cortically evoked responses. This suggests the existence of functional channels that allow for the processing of different motor commands or information related to different body parts in parallel. Neurological disorders such as Parkinson's disease are associated with pathological activity in the BG and impaired synaptic connectivity, together with reorganization of somatotopic maps. One hypothesis is that motor symptoms are, at least partly, caused by an impairment of network structure perturbing the organization of functional channels. We developed a computational model of the STN-GPe circuit, a central part of the BG. By removing individual synaptic connections, we analyzed the contribution of signals propagating along different pathways to cortically evoked responses. We studied how evoked responses are affected by systematic changes in the network structure. To quantify the BG's organization in the form of functional channels, we suggested a two-site stimulation protocol. Our model reproduced the cortically evoked responses of STN and GPe neurons and the contributions of different pathways suggested by experimental studies. Cortical stimulation evokes spatio-temporal response patterns that are linked to the underlying synaptic network structure. Our two-site stimulation protocol yielded an approximate functional channel width. The presented results provide insight into the organization of BG synaptic connectivity, which is important for the development of computational models. The synaptic network structure strongly affects the processing of cortical signals and may impact the generation of pathological rhythms. Our work may motivate further experiments to analyze the network structure of BG nuclei and their organization in functional channels.

AI-enabled Hybrid Model for Lower-Limb Movements Recognition using Estimated Muscular Activity from Cortical Brain Signals

Decades of research determined electromyography (EMG) and electroencephalography (EEG), individually, as paramount controls aimed at rehabilitation. However, correlating commands from the central nervous system to lower-limb movements are highly complex raising challenges for anthropomorphic lower-limb prosthesis control. This work establishes a hierarchical relationship between 12-channel EEG and 4-channel surface EMG using a hybrid model (LRG-2L-LSTM) for lower-limb ankle movement recognition by estimating muscular activity from cortical brain signals. The proposed model achieved R 2 = 0.742 ± 0.03, RMSE = 0.067 ± 0.002 for EMG estimation and averaged recognition accuracy of 84.86 ± 0.27% for ankle movements using estimated EMG, thereby, establishing lower-limb prosthesis and exoskeleton control for amputees with little to no muscular strength.

Subjective feeling of control during fNIRS-based neurofeedback targeting the DL-PFC is related to neural activation determined with short-channel correction.

Neurofeedback (NF) training is a promising preventive and therapeutic approach for brain and behavioral impairments, the dorsolateral prefrontal cortex (DL-PFC) being a relevant region of interest. Functional near-infrared spectroscopy (NIRS) has recently been applied in NF training. However, this approach is highly sensitive to extra-cerebral vascularization, which could bias measurements of cortical activity. Here, we examined the feasibility of a NF training targeting the DL-PFC and its specificity by assessing the impact of physiological confounds on NF success via short-channel offline correction under different signal filtering conditions. We also explored whether the individual mental strategies affect the NF success. Thirty volunteers participated in a single 15-trial NF session in which they had to increase the oxy-hemoglobin (HbO2) level of their bilateral DL-PFC. We found that 0.01-0.09 Hz band-pass filtering was more suited than the 0.01-0.2 Hz band-pass filter to highlight brain activation restricted to the NF channels in the DL-PFC. Retaining the 10 out of 15 best trials, we found that 18 participants (60%) managed to control their DL-PFC. This number dropped to 13 (43%) with short-channel correction. Half of the participants reported a positive subjective feeling of control, and the "cheering" strategy appeared to be more effective in men (p<0.05). Our results showed successful DL-PFC fNIRS-NF in a single session and highlighted the value of accounting for extra cortical signals, which can profoundly affect the success and specificity of NF training.

Hierarchical Classification Strategy for Mitigating the Impact of The Presence of Pain in fNIRS-based BCIs.

Brain computer interfaces (BCIs) can find applications in assistive systems for patients who experience conditions that impede their motor abilities. A BCI uses signals acquired from the brain to control external devices. As physical pain influences cortical signals, the presence of pain can negatively impact the performance of the BCI. In this work, we propose a strategy to mitigate this negative impact. Cortical signals are acquired from test subjects while they performed two mental arithmetic tasks, in the presence and the absence of painful stimuli. The task of the BCI is to reliably classify the two mental arithmetic tasks from the cortical recordings, irrespective of the presence or the absence of pain. We propose to do this classification, hierarchically, in two levels. In the first level, the data is classified into those captured in the presence and the absence of pain. Depending on the results of the classification from the first level, in the second level, the BCI performs the classification of tasks using a classifier trained either in the presence or the absence of pain. A 1-dimensional convolutional neural network (1D-CNN) is used for classification at both levels. It is observed that using this hierarchical strategy, the BCI is able to classify the tasks with an accuracy greater than 90%, irrespective of the presence or the absence of pain. Given that the presence of physical pain has shown previously to reduce the classification accuracy of a BCI to almost chance levels, this mitigation strategy will be a significant step towards enhancing the performance of BCIs when they are used in assistive systems for patients.

The Spatial Precision of Contextual Feedback Signals in Human V1.

Neurons in the primary visual cortex (V1) receive sensory inputs that describe small, local regions of the visual scene and cortical feedback inputs from higher visual areas processing the global scene context. Investigating the spatial precision of this visual contextual modulation will contribute to our understanding of the functional role of cortical feedback inputs in perceptual computations. We used human functional magnetic resonance imaging (fMRI) to test the spatial precision of contextual feedback inputs to V1 during natural scene processing. We measured brain activity patterns in the stimulated regions of V1 and in regions that we blocked from direct feedforward input, receiving information only from non-feedforward (i.e., feedback and lateral) inputs. We measured the spatial precision of contextual feedback signals by generalising brain activity patterns across parametrically spatially displaced versions of identical images using an MVPA cross-classification approach. We found that fMRI activity patterns in cortical feedback signals predicted our scene-specific features in V1 with a precision of approximately 4 degrees. The stimulated regions of V1 carried more precise scene information than non-stimulated regions; however, these regions also contained information patterns that generalised up to 4 degrees. This result shows that contextual signals relating to the global scene are similarly fed back to V1 when feedforward inputs are either present or absent. Our results are in line with contextual feedback signals from extrastriate areas to V1, describing global scene information and contributing to perceptual computations such as the hierarchical representation of feature boundaries within natural scenes.

Structural and molecular cholinergic imaging markers of cognitive decline in Parkinson's disease.

Cognitive decline in Parkinson's disease is related to cholinergic system degeneration, which can be assessed in vivo using structural MRI markers of basal forebrain volume and PET measures of cortical cholinergic activity. In the present study we aimed to examine the interrelation between basal forebrain degeneration and PET-measured depletion of cortical acetylcholinesterase activity as well as their relative contribution to cognitive impairment in Parkinson's disease. This cross-sectional study included 143 Parkinson's disease participants without dementia and 52 healthy control participants who underwent structural MRI, PET scanning with 11C-methyl-4-piperidinyl propionate (PMP) as a measure of cortical acetylcholinesterase activity, and a detailed cognitive assessment. Based on the fifth percentile of the overall cortical PMP PET signal from the control group, people with Parkinson's disease were subdivided into a normo-cholinergic (n = 94) and a hypo-cholinergic group (n = 49). Volumes of functionally defined posterior and anterior basal forebrain subregions were extracted using an established automated MRI volumetry approach based on a stereotactic atlas of cholinergic basal forebrain nuclei. We used Bayesian t-tests to compare basal forebrain volumes between controls, and normo- and hypo-cholinergic Parkinson's participants after covarying out age, sex and years of education. Associations between the two cholinergic imaging measures were assessed across all people with Parkinson's disease using Bayesian correlations and their respective relations with performance in different cognitive domains were assessed with Bayesian ANCOVAs. As a specificity analysis, hippocampal volume was added to the analysis. We found evidence for a reduction of posterior basal forebrain volume in the hypo-cholinergic compared to both normo-cholinergic Parkinson's disease [Bayes factor against the null model (BF10) = 8.2] and control participants (BF10 = 6.0), while for the anterior basal forebrain the evidence was inconclusive (BF10 < 3). In continuous association analyses, posterior basal forebrain volume was significantly associated with cortical PMP PET signal in a temporo-posterior distribution. The combined models for the prediction of cognitive scores showed that both cholinergic markers (posterior basal forebrain volume and cortical PMP PET signal) were independently related to multi-domain cognitive deficits, and were more important predictors for all cognitive scores, including memory scores, than hippocampal volume. We conclude that degeneration of the posterior basal forebrain in Parkinson's disease is accompanied by functional cortical changes in acetylcholinesterase activity and that both PET and MRI cholinergic imaging markers are independently associated with multi-domain cognitive deficits in Parkinson's disease without dementia. Comparatively, hippocampal atrophy only seems to have minimal involvement in the development of early cognitive impairment in Parkinson's disease.

EEG decoding reveals neural predictions for naturalistic material behaviors.

Material properties like softness or stickiness determine how an object can be used. Based on our real-life experience, we form strong expectations about how objects should behave under force, given their typical material properties. Such expectations have been shown to modulate perceptual processes, but we currently do not know how expectation influences the temporal dynamics of the cortical visual analysis for objects and their materials. Here, we tracked the neural representations of expected and unexpected material behaviors using time-resolved EEG decoding in a violation-of-expectation paradigm, where objects fell to the ground and deformed in expected or unexpected ways. Participants were 25 men and women. Our study yielded three key results: First, both objects and materials were represented rapidly and in a temporally sustained fashion. Second, objects exhibiting unexpected material behaviors were more successfully decoded than objects exhibiting expected behaviors within 190ms after the impact, which might indicate additional processing demands when expectations are unmet. Third, general signals of expectation fulfillment that generalize across specific objects and materials were found within the first 150ms after the impact. Together, our results provide new insights into the temporal neural processing cascade that underlies the analysis of real-world material behaviors. They reveal a sequence of predictions, with cortical signals progressing from a general signature of expectation fulfillment towards increased processing of unexpected material behaviors.Significance Statement:In the real world, we can make accurate predictions about how an object's material shapes its behavior: For instance, we know that cups are typically made of porcelain and shatter when we accidentally drop them. Here, we use EEG to experimentally test how expectations about material behaviors impact neural processing. We showed our participants videos of objects that exhibited expected material behaviors (such as a glass shattering when falling to the ground) or unexpected material behaviors (such as a glass melting upon impact). Our results reveal a hierarchy of predictions in cortex: The visual system rapidly generates signals that index whether expectations about material behaviors are met. These signals are followed by increased processing of objects displaying unexpected material behaviors.

Physiological modeling of the BOLD signal and implications for effective connectivity: A primer

In this primer, I provide an overview of the physiological processes that contribute to the observed BOLD signal (i.e., the generative biophysical model), including their time course properties within the framework of the physiologically-informed dynamic causal modeling (P-DCM). The BOLD signal is primarily determined by the change in paramagnetic deoxygenated hemoglobin, which results from combination of changes in oxygen metabolism, and cerebral blood flow and volume. Specifically, the physiological origin of the so-called BOLD signal “transients” will be discussed, including the initial overshoot, steady-state activation and the post-stimulus undershoot. I argue that incorrect physiological assumptions in the generative model of the BOLD signal can lead to incorrect inferences pertaining to both local neuronal activity and effective connectivity between brain regions. In addition, I introduce the recent laminar BOLD signal model, which extends P-DCM to cortical depths-resolved BOLD signals, allowing for laminar neuronal activity to be determined using high-resolution fMRI data.

CEST 2022-three-dimensional amide proton transfer (APT) imaging can identify the changes of cerebral cortex in Parkinson's disease

PurposeAmide proton transfer (APT) imaging has shown its diagnostic and predictive superiority in Parkinson's disease (PD) in our previous studies using 2D APT imaging based on deep nuclei. We hypothesized that the pathophysiological abnormality of PD will change the APT-related parameters in the cerebral cortex, and the signal changes can contribute to accurate diagnosis of PD. Methods34 patients with idiopathic Parkinson's disease (IPD) and 29 age- and sex-matched normal controls (NC) were enrolled in this prospective study. 3D-APT imaging and 3D-T1WI was performed in our participants. A volume-based morphometry algorithm was used and get automated cortical segmentations. Quantitative parameter maps of APT-related metrics were calculated by using SPM and MATLAB. The unpaired Student's t-test or Mann-Whitney U test was used for comparison of these values between IPD and NC groups. The associations between APT-related metrics and clinical assessments were investigated by Spearman correlation analysis. The receiver-operating characteristic (ROC) analysis was used to assess the diagnostic performances. The binary logistic regression model was used to combine the imaging parameters. ResultsThere wasn't any correlations between cortical APT-related signals and clinical assessment, including the H&Y scale, the disease duration, the UPDRS III scores and the MMSE scores. The MTRasym, CESTRnr and MTRRex had significantly higher values (p <0.001, corrected by Bonferroni methods) in the IPD group than NC groups in the region of bilateral and total temporal grey matter. The single parameters achieved the best diagnostic performance among all APT-related metrics was MTRRex on the right temporal grey matter, with an area under the ROC curve (AUC) of 0.865. The combined parameters achieved the highest diagnostic performance (AUC: 0.932). Conclusions3D-APT imaging could identify the changes of the cerebral cortex in Parkinson's disease. The cortical changes of APT-related parameters could potentially serve as imaging biomarkers to aid in the non-invasive diagnosis of PD.

Interacting spiral wave patterns underlie complex brain dynamics and are related to cognitive processing.

The large-scale activity of the human brain exhibits rich and complex patterns, but the spatiotemporal dynamics of these patterns and their functional roles in cognition remain unclear. Here by characterizing moment-by-moment fluctuations of human cortical functional magnetic resonance imaging signals, we show that spiral-like, rotational wave patterns (brain spirals) are widespread during both resting and cognitive task states. These brain spirals propagate across the cortex while rotating around their phase singularity centres, giving rise to spatiotemporal activity dynamics with non-stationary features. The properties of these brain spirals, such as their rotational directions and locations, are task relevant and can be used to classify different cognitive tasks. We also demonstrate that multiple, interacting brain spirals are involved in coordinating the correlated activations and de-activations of distributed functional regions; this mechanism enables flexible reconfiguration of task-driven activity flow between bottom-up and top-down directions during cognitive processing. Our findings suggest that brain spirals organize complex spatiotemporal dynamics of the human brain and have functional correlates to cognitive processing.

Characteristics of resting state functional connectivity of motor cortex of high fitness level college students: Experimental evidence from functional near infrared spectroscopy (fNIRS)

AbstractObjectiveThis study inspects difference of resting state functional connectivity (RSFC) of motor cortex between athletes and ordinary college students and the test‐retest reliability of RSFC.MethodsTwenty high fitness level college students (high fitness group) and 20 ordinary college students (control group) were recruited. The motor cortical blood oxygen signals in resting states were monitored by functional near infrared spectroscopy (fNIRS). RSFCs of brain signals were preprocessed and calculated by FC‐NIRS software. RSFC results of test‐retest reliability were evaluated by intra‐class correlation coefficient (ICC).ResultsTotal RSFC (HbO signal) was significantly different between high fitness group (0.62 ± 0.04) and low fitness group (0.81 ± 0.04) (p &lt; .05). Significant differences were found between the groups (HbO signal) in 50 edges among the 190 edges of motor cortex (14 edges after FDR corrected). At three hemoglobin concentrations, mean of group‐level ICC (C, 1) for total RSFC in two groups was 0.40 ± 0.10, whereas the mean of group‐level ICC (C, k) was 0.57 ± 0.11, depicting “fair” reliability. The mean of group‐level ICC (C, 1) of 190 “edges” was 0.88 ± 0.06, whereas mean of ICC (C, k) was 0.94 ± 0.03, exhibiting “excellent” reliability.ConclusionFitness level is the factor causing specific changes in RSFC strength of motor cortex that can be utilized as biomarker for evaluating the fitness level.

Increments in visual motion coherence are more readily detected than decrements.

Understanding the circuits that access and read out information in the cerebral cortex to guide behavior remains a challenge for systems-level neuroscience. Recent optogenetic experiments targeting specific cell classes in mouse primary visual cortex (V1) have shown that mice are sensitive to optically-induced increases in V1 spiking but are relatively insensitive to decreases in neuronal spiking of similar magnitude and time course. This asymmetry suggests that the readout of signals from cortex depends preferentially on increases in spike rate. We investigated whether humans display a similar asymmetry by measuring thresholds for detecting changes in the motion coherence of dynamic random dot stimuli. The middle temporal visual area (MT) has been shown to play an important role in discriminating random dot stimuli, and the responses of its individual neurons to dynamic random dots are well characterized. Although both increments and decrements in motion coherence have heterogeneous effects on MT responses, increments cause on average more increases in firing rates. Consistent with this, we found that subjects are more sensitive to increments of random dot motion coherence than to decrements of coherence. The magnitude of the difference in detectability was consistent with the expected difference in neuronal signal-to-noise associated with MT spike rate increases driven by coherence increments and decrements. The results add strength to the notion that the circuit mechanisms that read out cortical signals are relatively insensitive to decrements in cortical spiking.

MR imaging differentiating features between lytic and degenerative lumbosacral spondylolisthesis.

Spondylolisthesis is characterized by the displacement of one vertebral body in relation to the adjacent vertebra. It is commonly observed in the lower lumbar region and can be caused by a variety of factors, including spondylolysis (a fracture in the pars interarticularis) or degenerative disease. Magnetic resonance imaging (MRI) is becoming increasingly popular as the primary modality for evaluation of low back pain and is often used in the absence of radiographs or Computed Tomography. However, it can be challenging for radiologists to differentiate between the two types of spondylolisthesis based on MRI alone. The goal of this article is to identify key imaging features on MRI that can aid radiologists in differentiating between spondylolysis and degenerative spondylolisthesis on MRI. Five key concepts are discussed: the "step-off" sign, the "wide canal" sign, T2 cortical bone signal on MRI, epidural fat interposition, and fluid in the facet joints. The utility, limitations and potential pitfalls of these concepts are also discussed to provide a comprehensive understanding of their use in differentiating between the two types of spondylolisthesis on MRI.

Monosynaptic trans-collicular pathways link mouse whisker circuits to integrate somatosensory and motor cortical signals.

The superior colliculus (SC), a conserved midbrain node with extensive long-range connectivity throughout the brain, is a key structure for innate behaviors. Descending cortical pathways are increasingly recognized as central control points for SC-mediated behaviors, but how cortico-collicular pathways coordinate SC activity at the cellular level is poorly understood. Moreover, despite the known role of the SC as a multisensory integrator, the involvement of the SC in the somatosensory system is largely unexplored in comparison to its involvement in the visual and auditory systems. Here, we mapped the connectivity of the whisker-sensitive region of the SC in mice with trans-synaptic and intersectional tracing tools and in vivo electrophysiology. The results reveal a novel trans-collicular connectivity motif in which neurons in motor- and somatosensory cortices impinge onto the brainstem-SC-brainstem sensory-motor arc and onto SC-midbrain output pathways via only one synapse in the SC. Intersectional approaches and optogenetically assisted connectivity quantifications in vivo reveal convergence of motor and somatosensory cortical input on individual SC neurons, providing a new framework for sensory-motor integration in the SC. More than a third of the cortical recipient neurons in the whisker SC are GABAergic neurons, which include a hitherto unknown population of GABAergic projection neurons targeting thalamic nuclei and the zona incerta. These results pinpoint a whisker region in the SC of mice as a node for the integration of somatosensory and motor cortical signals via parallel excitatory and inhibitory trans-collicular pathways, which link cortical and subcortical whisker circuits for somato-motor integration.

Detection of grey matter microstructural substrates of neurodegeneration in multiple sclerosis.

Multiple sclerosis features complex pathological changes in grey matter that begin early and eventually lead to diffuse atrophy. Novel approaches to image grey-matter microstructural alterations in vivo are highly sought after and would enable more sensitive monitoring of disease activity and progression. This cross-sectional study aimed to assess the sensitivity of high-gradient diffusion MRI for microstructural tissue damage in cortical and deep grey matter in people with multiple sclerosis and test the hypothesis that reduced cortical cell body density is associated with cortical and deep grey-matter volume loss. Forty-one people with multiple sclerosis (age 24-72, 14 females) and 37 age- and sex-matched healthy controls were scanned on a 3 T Connectom MRI scanner equipped with 300 mT/m gradients using a multi-shell diffusion MRI protocol. The soma and neurite density imaging model was fitted to high-gradient diffusion MRI data to obtain estimates of intra-neurite, intra-cellular and extra-cellular signal fractions and apparent soma radius. Cortical and deep grey-matter microstructural imaging metrics were compared between multiple sclerosis and healthy controls and correlated with grey-matter volume, clinical disability and cognitive outcomes. People with multiple sclerosis showed significant cortical and deep grey-matter volume loss compared with healthy controls. People with multiple sclerosis showed trends towards lower cortical intra-cellular signal fraction and significantly lower intra-cellular and higher extra-cellular signal fractions in deep grey matter, especially the thalamus and caudate, compared with healthy controls. Changes were most pronounced in progressive disease and correlated with the Expanded Disability Status Scale, but not the Symbol Digit Modalities Test. In multiple sclerosis, normalized thalamic volume was associated with thalamic microstructural imaging metrics. Whereas thalamic volume loss did not correlate with cortical volume loss, cortical microstructural imaging metrics were significantly associated with thalamic volume, and not with cortical volume. Compared with the short diffusion time (Δ = 19 ms) achievable on the Connectom scanner, at the longer diffusion time of Δ = 49 ms attainable on clinical scanners, multiple sclerosis-related changes in imaging metrics were generally less apparent with lower effect sizes in cortical and deep grey matter. Soma and neurite density imaging metrics obtained from high-gradient diffusion MRI data provide detailed grey-matter characterization beyond cortical and thalamic volumes and distinguish multiple sclerosis-related microstructural pathology from healthy controls. Cortical cell body density correlates with thalamic volume, appears sensitive to the microstructural substrate of neurodegeneration and reflects disability status in people with multiple sclerosis, becoming more pronounced as disability worsens.

Gray Matter Microstructure Alterations in People with Multiple Sclerosis Based on Cell Body and Neurite Density Imaging (P10-3.007)

<h3>Objective:</h3> To evaluate a novel compartment-based model for apparent cell body and neurite density imaging (SANDI) in gray matter (GM) in people with multiple sclerosis (MS) compared to healthy controls (HC) and its correlation with brain atrophy. <h3>Background:</h3> MS features focal cortical lesions and microstructural changes in normal-appearing GM, which can impact clinical function and disability. High gradient diffusion MRI has potential to optimize GM tissue microstructure characterization by overcoming challenges due to the complexity of underlying components. <h3>Design/Methods:</h3> 41 people with MS and 37 age- and sex-matched HC were scanned on a 3T Connectom MRI scanner equipped with 300mT/m gradients using a multi-shell acquisition protocol consisting of eight b-values at 19msec diffusion time. Microstructural metrics of SANDI, including a measure of soma density (f_soma) in the cortex and deep GM, were compared between MS and HC and correlated with cortical and thalamic atrophy, correcting for multiple comparisons. <h3>Results:</h3> Cortical cell body signal fraction (f_soma) was decreased in MS compared to HC (0.56 vs. 0.58, <i>p</i>=0.027, not surviving FDR-correction). In deep GM, f_soma and extra-cellular signal fraction were significantly decreased in MS compared to HC (<i>FDR-p</i>=0.045 in both), which was most pronounced in progressive MS. Based on spatial analysis, f_soma of caudate nucleus and thalamus were significantly decreased in MS compared to HC (<i>FDR-p</i>=0.003 and <i>FDR-p</i>=0.027, respectively). Whereas cortical atrophy in MS was poorly correlated with cortical f_soma, thalamic atrophy in MS demonstrated moderate correlation with decreased thalamic f_soma (r=0.311, <i>p</i>=0.054) and decreased cortical f_soma (r=0.474, <i>p</i>=0.008). <h3>Conclusions:</h3> SANDI metrics, in particular f_soma, provide detailed GM characterization beyond cortical and thalamic volumes and are able to characterize MS-related microstructural pathology. Decreased cortical cell density correlates with declining thalamic volume and may precede volumetric measures of cortical atrophy in people with MS. <b>Disclosure:</b> Ms. Krijnen has nothing to disclose. Andrew Russo has nothing to disclose. Dr. Salim Karam has nothing to disclose. The institution of Menno M Schoonheim has received research support from Dutch MS Research Foundation. The institution of Menno M Schoonheim has received research support from Eurostars-EUREKA. The institution of Menno M Schoonheim has received research support from ARSEP. The institution of Menno M Schoonheim has received research support from Amsterdam Neuroscience. The institution of Menno M Schoonheim has received research support from MAGNIMS. The institution of Menno M Schoonheim has received research support from ZonMW. The institution of Menno M Schoonheim has received research support from Atara Biotherapeutics. The institution of Menno M Schoonheim has received research support from Biogen. The institution of Menno M Schoonheim has received research support from Celgene/Bristol Meyers Squibb. The institution of Menno M Schoonheim has received research support from Genzyme. The institution of Menno M Schoonheim has received research support from MedDay. The institution of Menno M Schoonheim has received research support from Merck. Dr. Huang has received personal compensation in the range of $0-$499 for serving as a Consultant for Siemens Healthineers. The institution of Dr. Huang has received research support from Siemens Healthineers. The institution of Dr. Huang has received research support from Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School. Dr. Klawiter has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Galen/Atlantica. Dr. Klawiter has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Genentech. Dr. Klawiter has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Banner Life Sciences. Dr. Klawiter has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Greenwich Biosciences. Dr. Klawiter has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for OM1. Dr. Klawiter has received personal compensation in the range of $500-$4,999 for serving on a Scientific Advisory or Data Safety Monitoring board for TG Therapeutics. The institution of Dr. Klawiter has received research support from Biogen. The institution of Dr. Klawiter has received research support from Abbvie. The institution of Dr. Klawiter has received research support from Genentech.