Cortical Neural Activity Research Articles

Brain state and cortical layer-specific mechanisms underlying perception at threshold

Identical stimuli can be perceived or go unnoticed across successive presentations, producing divergent behavioral outcomes despite similarities in sensory input. We sought to understand how fluctuations in behavioral state and cortical layer and cell class-specific neural activity underlie this perceptual variability. We analyzed physiological measurements of state and laminar electrophysiological activity in visual area V4 while monkeys were rewarded for correctly reporting a stimulus change at perceptual threshold. Hit trials were characterized by a behavioral state with heightened arousal, greater eye position stability, and enhanced decoding performance of stimulus identity from neural activity. Target stimuli evoked stronger responses in V4 in hit trials, and excitatory neurons in the superficial layers, the primary feed-forward output of the cortical column, exhibited lower variability. Feed-forward interlaminar population correlations were stronger on hits. Hit trials were further characterized by greater synchrony between the output layers of the cortex during spontaneous activity, while the stimulus-evoked period showed elevated synchrony in the feed-forward pathway. Taken together, these results suggest that a state of elevated arousal and stable retinal images allow enhanced processing of sensory stimuli, which contributes to hits at perceptual threshold.

An Accurate and Rapidly Calibrating Speech Neuroprosthesis

BackgroundBrain–computer interfaces can enable communication for people with paralysis by transforming cortical activity associated with attempted speech into text on a computer screen. Communication with brain–computer interfaces has been restricted by extensive training requirements and limited accuracy.MethodsA 45-year-old man with amyotrophic lateral sclerosis (ALS) with tetraparesis and severe dysarthria underwent surgical implantation of four microelectrode arrays into his left ventral precentral gyrus 5 years after the onset of the illness; these arrays recorded neural activity from 256 intracortical electrodes. We report the results of decoding his cortical neural activity as he attempted to speak in both prompted and unstructured conversational contexts. Decoded words were displayed on a screen and then vocalized with the use of text-to-speech software designed to sound like his pre-ALS voice.ResultsOn the first day of use (25 days after surgery), the neuroprosthesis achieved 99.6% accuracy with a 50-word vocabulary. Calibration of the neuroprosthesis required 30 minutes of cortical recordings while the participant attempted to speak, followed by subsequent processing. On the second day, after 1.4 additional hours of system training, the neuroprosthesis achieved 90.2% accuracy using a 125,000-word vocabulary. With further training data, the neuroprosthesis sustained 97.5% accuracy over a period of 8.4 months after surgical implantation, and the participant used it to communicate in self-paced conversations at a rate of approximately 32 words per minute for more than 248 cumulative hours.ConclusionsIn a person with ALS and severe dysarthria, an intracortical speech neuroprosthesis reached a level of performance suitable to restore conversational communication after brief training. (Funded by the Office of the Assistant Secretary of Defense for Health Affairs and others; BrainGate2 ClinicalTrials.gov number, NCT00912041.)

Effects of Phasic Activation of Locus Ceruleus on Cortical Neural Activity and Auditory Discrimination Behavior.

Although the locus ceruleus (LC) is recognized as a crucial modulator for attention and perception by releasing norepinephrine into various cortical regions, the impact of LC-noradrenergic (LC-NE) modulation on auditory discrimination behavior remains elusive. In this study, we firstly recorded local field potential and single-unit activity in multiple cortical regions associated with auditory-motor processing, including the auditory cortex, posterior parietal cortex, secondary motor cortex, anterior cingulate cortex, prefrontal cortex, and orbitofrontal cortex (OFC), in response to optogenetic activation (40 Hz and 0.5 s) of the LC-NE neurons in awake mice (male). We found that phasic LC stimulation induced a persistent high gamma oscillation (50-80 Hz) in the OFC. Phasic activation of LC-NE neurons also resulted in a corresponding increase in norepinephrine levels in the OFC, accompanied by a pupillary dilation response. Furthermore, when mice were performing a go/no-go auditory discrimination task, we optogeneticaly activated the neural projections from LC to OFC and revealed a shortened latency in behavioral responses to sound stimuli and an increased false alarm rate. These impulsive behavioral responses may be associated with the gamma neural activity in the OFC. These findings have broadened our understanding of the neural mechanisms involved in the role of LC in auditory-motor processing.

Abnormal resting-state hyperconnectivity in schizophrenia: A whole-head near-infrared spectroscopy study

Near-infrared spectroscopy (NIRS) is a noninvasive functional neuroimaging modality that can detect changes in blood oxygenation levels by tracking cortical neural activity. We recorded the resting-state brain activity of 24 individuals with schizophrenia and 90 healthy controls for 8 min using a whole-head NIRS arrangement and then used partial correlation analysis to estimate the resting-state functional connectivity (RSFC) between 17 cortical regions. We found that the RSFC between the bilateral orbitofrontal cortices (OFCs) and between the right temporal and parietal lobes was significantly higher in patients with schizophrenia than in healthy controls. The RSFC between the bilateral OFCs was positively correlated with negative symptom severity, whereas the RSFC between the right temporal and parietal lobes was positively correlated with the chlorpromazine equivalent for antipsychotics prescribed to patients with schizophrenia. This finding was consistent with that for the RSFC calculated using the anterior 52-channel signals. Our results suggest that NIRS-based RSFC measurements have potential clinical applications.

Neuromodulatory Compensation of Cortical Neural Activity on Electrodeposited Pt/Ir Modified Microelectrode Arrays for Temperature Transients.

Temperature has a profound influence on various neuromodulation processes and has emerged as a focal point. However, the effects of acute environmental temperature fluctuations on cultured cortical networks have been inadequately elucidated. To bridge this gap, we have developed a brain-on-a-chip platform integrating cortical networks and electrodeposited Pt/Ir modified microelectrode arrays (MEAs) with 3D-printed bear-shaped triple chambers, facilitating control of temperature transients. This innovative system administers thermal stimuli while concurrently monitoring neuronal activity, including spikes and local field potentials, from 60 microelectrodes (diameter: 30 μm; impedance: 9.34 ± 1.37 kΩ; and phase delay: -45.26 ± 2.85°). Temperature transitions of approximately ±10 °C/s were applied to cortical networks on MEAs via in situ perfusion within the triple chambers. Subsequently, we examined the spatiotemporal dynamics of the brain-on-a-chip under temperature regulation at both the group level (neuronal population) and their interactions (network dynamics) and the individual level (cellular activity). Specifically, we found that after the temperature reduction neurons enhanced the overall information transmission efficiency of the network through synchronous firing to compensate for the decreased efficiency of single-cell level information transmission, in contrast to temperature elevation. By leveraging the integration of high-performance MEAs with perfusion chambers, this investigation provides a comprehensive understanding of the impact of temperature on the spatiotemporal dynamics of neural networks, thereby facilitating future exploration of the intricate interplay between temperature and brain function.

Cerebral Cortical Surface Structure and Neural Activation Pattern Among Adolescent Football Players

Recurring exposure to head impacts in American football has garnered public and scientific attention, yet neurobiological associations in adolescent football players remain unclear. To examine cortical structure and neurophysiological characteristics in adolescent football players. This cohort study included adolescent football players and control athletes (swimming, cross country, and tennis) from 5 high school athletic programs, who were matched with age, sex (male), and school. Neuroimaging assessments were conducted May to July of the 2021 and 2022 seasons. Data were analyzed from February to November 2023. Playing tackle football or noncontact sports. Structural magnetic resonance imaging (MRI) data were analyzed for cortical thickness, sulcal depth, and gyrification, and cortical surface-based resting state (RS)-functional MRI analyses examined the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and RS-functional connectivity (RS-FC). Two-hundred seventy-five male participants (205 football players; mean [SD] age, 15.8 [1.2] years; 5 Asian [2.4%], 8 Black or African American [3.9%], and 189 White [92.2%]; 70 control participants; mean [SD] age 15.8 [1.2] years, 4 Asian [5.7], 1 Black or African American [1.4%], and 64 White [91.5%]) were included in this study. Relative to the control group, the football group showed significant cortical thinning, especially in fronto-occipital regions (eg, right precentral gyrus: t = -2.24; P = .01; left superior frontal gyrus: -2.42; P = .002). Elevated cortical thickness in football players was observed in the anterior and posterior cingulate cortex (eg, left posterior cingulate cortex: t = 2.28; P = .01; right caudal anterior cingulate cortex 3.01; P = .001). The football group had greater and deeper sulcal depth than the control groups in the cingulate cortex, precuneus, and precentral gyrus (eg, right inferior parietal lobule: t = 2.20; P = .004; right caudal anterior cingulate cortex: 4.30; P < .001). Significantly lower ALFF was detected in the frontal lobe and cingulate cortex of the football group (t = -3.66 to -4.92; P < .01), whereas elevated ALFF was observed in the occipital regions (calcarine and lingual gyrus, t = 3.20; P < .01). Similar to ALFF, football players exhibited lower ReHo in the precentral gyrus and medial aspects of the brain, such as precuneus, insula, and cingulum, whereas elevated ReHo was clustered in the occipitotemporal regions (t = 3.17; P < .001; to 4.32; P < .01). There was no group difference in RS-FC measures. In this study of adolescent athletes, there was evidence of discernible structural and physiological differences in the brains of adolescent football players compared with their noncontact controls. Many of the affected brain regions were associated with mental health well-being.

Degraded inferior colliculus responses to complex sounds in prenatally exposed VPA rats

BackgroundIndividuals with autism spectrum disorders (ASD) often exhibit altered sensory processing and deficits in language development. Prenatal exposure to valproic acid (VPA) increases the risk for ASD and impairs both receptive and expressive language. Like individuals with ASD, rodents prenatally exposed to VPA exhibit degraded auditory cortical processing and abnormal neural activity to sounds. Disrupted neuronal morphology has been documented in earlier processing areas of the auditory pathway in VPA-exposed rodents, but there are no studies documenting early auditory pathway physiology. Therefore, the objective of this study is to characterize inferior colliculus (IC) responses to different sounds in rats prenatally exposed to VPA compared to saline-exposed rats.MethodsIn vivo extracellular multiunit recordings from the inferior colliculus were collected in response to tones, speech sounds, and noise burst trains.ResultsOur results indicate that the overall response to speech sounds was degraded in VPA-exposed rats compared to saline-exposed controls, but responses to tones and noise burst trains were unaltered.ConclusionsThese results are consistent with observations in individuals with autism that neural responses to complex sounds, like speech, are often altered, and lays the foundation for future studies of potential therapeutics to improve auditory processing in the VPA rat model of ASD.

Explainable Deep-Learning Prediction for Brain-Computer Interfaces Supported Lower Extremity Motor Gains Based on Multistate Fusion.

Predicting the potential for recovery of motor function in stroke patients who undergo specific rehabilitation treatments is an important and major challenge. Recently, electroencephalography (EEG) has shown potential in helping to determine the relationship between cortical neural activity and motor recovery. EEG recorded in different states could more accurately predict motor recovery than single-state recordings. Here, we design a multi-state (combining eyes closed, EC, and eyes open, EO) fusion neural network for predicting the motor recovery of patients with stroke after EEG-brain-computer-interface (BCI) rehabilitation training and use an explainable deep learning method to identify the most important features of EEG power spectral density and functional connectivity contributing to prediction. The prediction accuracy of the multi-states fusion network was 82%, significantly improved compared with a single-state model. The neural network explanation result demonstrated the important region and frequency oscillation bands. Specifically, in those two states, power spectral density and functional connectivity were shown as the regions and bands related to motor recovery in frontal, central, and occipital. Moreover, the motor recovery relation in bands, the power spectrum density shows the bands at delta and alpha bands. The functional connectivity shows the delta, theta, and alpha bands in the EC state; delta, theta, and beta mid at the EO state are related to motor recovery. Multi-state fusion neural networks, which combine multiple states of EEG signals into a single network, can increase the accuracy of predicting motor recovery after BCI training, and reveal the underlying mechanisms of motor recovery in brain activity.

Electrophysiological correlates of the emotional response on brain activity in adolescents

Many studies have attempted to analyze the main neurophysiological characteristics of emotional response, but few have been carried out at early ages, including adolescence or early adulthood. The main objective of the present study is to assess the electrophysiological correlates of emotional response in adolescents and young adults through electroencephalography (EEG) measures. Sample, composed of 25 subjects (18.44 ± 0.71 years old), were exposed to different sequences of images belonging to the IAPS, which were selected following the dimensional model, based on their valence and arousal, while their neural activity was evaluated through EEG. Results indicated differences in cortical neural activity in response to the valence of the images and the level of arousal. Specifically, we observed that exposure to positive images (high valence) with high arousal produced an increase in alpha, beta, and delta wave activity but not in theta activity. In the case of positive images with low arousal, however, the results indicated an increase in beta waves only and a decrease in alpha, delta, and theta activity. For negative images (low valence) with high arousal, an increase in alpha, beta, and delta waves but not in theta was observed, while negative images with low arousal induced an increase in beta, delta, and theta wave response. This study demonstrates that activated cortical areas indicated significant differences based on the different emotional responses in adolescents and young adults.

Repetitive transcranial magnetic stimulation ameliorates symptoms in patients with myalgic encephalomyelitis (chronic fatigue syndrome)

BackgroundCentral nervous system dysfunction has been postulated to cause debilitating symptoms in patients with myalgic encephalomyelitis (ME) (originally called “chronic fatigue syndrome”). Repetitive transcranial magnetic stimulation (rTMS) is a newly developed neuromodulatory procedure and has been suggested to facilitate the cortical neural activity. MethodsThis study enrolled 30 patients with ME (7 men and 23 women) with a mean age of 39 ± 12 years, who received rTMS treatment of both the left dorsolateral prefrontal cortex and the left primary motor area in the brain. The performance status score (0−9) for restricting activities of daily living, orthostatic intolerance (OI) during a 10-min standing test, neurologic disequilibrium diagnosed as unstable standing with their feet together and eyes closed, neuropathic pain or fibromyalgia, and muscle weakness were compared before and after treatment. ResultsAfter therapy, favorable effects were observed with a decrease in performance status score or index for restriction of activities of daily living of ≥ 2 points in 20 patients (67%). OI with the inability to complete the 10-min standing test was resolved in 10 (83%) out of 12 patients, and disequilibrium was resolved in 15 (88%) out of 17 patients. Neuropathic pain or fibromyalgia was attenuated in seven (70%) out of 10 patients. Muscle weakness with grip power of < 10 kg was resolved in two (50%) out of four patients. No untoward effects were encountered in all the study patients. ConclusionThe treatment with rTMS is effective in alleviating various symptoms, especially OI and disequilibrium, and in improving the activities of daily living in patients with ME.

The changes of neuroactivity of Tui Na (Chinese massage) at Hegu acupoint on sensorimotor cortex in stroke patients with upper limb motor dysfunction: a fNIRS study

BackgroundTui Na (Chinese massage) is a relatively simple, inexpensive, and non-invasive intervention, and has been used to treat stroke patients for many years in China. Tui Na acts on specific parts of the body which are called meridians and acupoints to achieve the role of treating diseases. Yet the underlying neural mechanism associated with Tui Na is not clear due to the lack of detection methods.ObjectiveFunctional near-infrared spectroscopy (fNIRS) was used to explore the changes of sensorimotor cortical neural activity in patients with upper limb motor dysfunction of stroke and healthy control groups during Tui Na Hegu Point.MethodsTen patients with unilateral upper limb motor dysfunction after stroke and eight healthy subjects received Tui Na. fNIRS was used to record the hemodynamic data in the sensorimotor cortex and the changes in blood flow were calculated based on oxygenated hemoglobin (Oxy-Hb), the task session involved repetitive Tui Na on Hegu acupoint, using a block design [six cycles: rest (20 seconds); Tui Na (20 seconds); rest (30 seconds)]. The changes in neural activity in sensorimotor cortex could be inferred according to the principle of neurovascular coupling, and the number of activated channels in the bilateral hemisphere was used to calculate the lateralization index.Result1. For hemodynamic response induced by Hegu acupoint Tui Na, a dominant increase in the contralesional primary sensorimotor cortex during Hegu point Tui Na of the less affected arm in stroke patients was observed, as well as that in healthy controls, while this contralateral pattern was absent during Hegu point Tui Na of the affected arm in stroke patients. 2. Concerning the lateralization index in stroke patients, a significant difference was observed between lateralization index values for the affected arm and the less affected arm (P < 0.05). Wilcoxon tests showed a significant difference between lateralization index values for the affected arm in stroke patients and lateralization index values for the dominant upper limb in healthy controls (P < 0.05), and no significant difference between lateralization index values for the less affected arm in stroke patients and that in healthy controls (P = 0.36).ConclusionThe combination of Tui Na and fNIRS has the potential to reflect the functional status of sensorimotor neural circuits. The changes of neuroactivity in the sensorimotor cortex when Tui Na Hegu acupoint indicate that there is a certain correlation between acupoints in traditional Chinese medicine and neural circuits.

Invited Session III: Neural network models of the visual system: Robust information representation in hierarchical networks of the visual cortex.

The mammalian visual system has an exquisite ability to encode relevant information from noisy sensory inputs in natural scenes. Such robust yet adaptable computation is believed to emerge from the uniquely complex connectivity structure of biological neural networks. In this talk, I will focus on the hierarchical organization of the cortical network, and discuss how this unique network structure shapes robust representations of noisy visual inputs via predictive coding. Using a predictive coding model of hierarchically-related visual cortical areas, we link feedback connections to top-down predictions of the lower cortical neural activity. Our model shows that hierarchical predictive coding explains the mechanisms of robust recognition of noisy objects in intermediate cortical areas. Secondly, we study how context-specific information may be represented and modified across learning in populations of neurons in a recurrent neural network model of hierarchically-related cortical areas. Motivated by an experimental study investigating neural activities in response to expected and unexpected natural images in mouse visual cortex, we test how the divergence of feedforward and feedback connections underlie differential representations of expected and surprising sensory information across cortical areas and layers. In sum, our study provides insights into how robust and adaptable visual encoding arise from biologically-motivated connectivity across the cortical hierarchy.

Hybrid predictive coding: Inferring, fast and slow.

Predictive coding is an influential model of cortical neural activity. It proposes that perceptual beliefs are furnished by sequentially minimising "prediction errors"-the differences between predicted and observed data. Implicit in this proposal is the idea that successful perception requires multiple cycles of neural activity. This is at odds with evidence that several aspects of visual perception-including complex forms of object recognition-arise from an initial "feedforward sweep" that occurs on fast timescales which preclude substantial recurrent activity. Here, we propose that the feedforward sweep can be understood as performing amortized inference (applying a learned function that maps directly from data to beliefs) and recurrent processing can be understood as performing iterative inference (sequentially updating neural activity in order to improve the accuracy of beliefs). We propose a hybrid predictive coding network that combines both iterative and amortized inference in a principled manner by describing both in terms of a dual optimization of a single objective function. We show that the resulting scheme can be implemented in a biologically plausible neural architecture that approximates Bayesian inference utilising local Hebbian update rules. We demonstrate that our hybrid predictive coding model combines the benefits of both amortized and iterative inference-obtaining rapid and computationally cheap perceptual inference for familiar data while maintaining the context-sensitivity, precision, and sample efficiency of iterative inference schemes. Moreover, we show how our model is inherently sensitive to its uncertainty and adaptively balances iterative and amortized inference to obtain accurate beliefs using minimum computational expense. Hybrid predictive coding offers a new perspective on the functional relevance of the feedforward and recurrent activity observed during visual perception and offers novel insights into distinct aspects of visual phenomenology.

Near-Infrared Spectroscopy: A Free-Living Neuroscience Tool to Better Understand Diabetes and Obesity.

The human brain is the least accessible of all organs and attempts to study it in vivo rely predominantly on neuroimaging. Functional near-infrared spectroscopy (fNIRS) allows for the study of cortical neural activity in a non-invasive manner that may resemble free-living conditions. Moreover, compared to other neuroimaging tools, fNIRS is less expensive, it does not require the use of ionizing radiation, and can be applied to all study populations (patients suffering from claustrophobia, or neonates). In this narrative review, we provide an overview of the available research performed using fNIRS in patients with diabetes and obesity. The few studies conducted to date have presented controversial results regarding patients with diabetes, some reporting a greater hemodynamic response and others reporting a reduced hemodynamic response compared to the controls, with an unclear distinction between types 1 and 2. Subjects with obesity or a binge eating disorder have reduced prefrontal activation in response to inhibitory food or non-food stimuli; however, following an intervention, such as cognitive treatment, prefrontal activation is restored. Moreover, we discuss the potential of future applications of fNIRS for a better understanding of cortical neural activity in the context of metabolic disorders.

Brain structure and cortical activity changes of new daily persistent headache: multimodal evidence from MEG/sMRI

BackgroundNew daily persistent headache (NDPH) is a rare but debilitating primary headache disorder that poses a significant burden on individuals and society. Despite its clinical importance, the underlying pathophysiological mechanisms of NDPH remain unclear. In this study, we aimed to investigate the brain structural changes and neural activity patterns in patients with NDPH using multimodal brain imaging analysis of structural magnetic resonance imaging (sMRI) combined with magnetoencephalography (MEG).MethodsTwenty-eight patients with NDPH and 37 healthy controls (HCs) were recruited for this study, and their structural and resting-state data were collected by 3.0 Tesla MRI and MEG. We analyzed the brain morphology using voxel-based morphometry and source-based morphometry. In each brain region, MEG sensor signals from 1 to 200 Hz were analyzed using an adapted version of Welch's method. MEG source localization was conducted using the dynamic statistical parametric mapping, and the difference of source distribution between patients with NDPH and HCs was examined.ResultsOur results revealed significant differences in the regional grey matter volume, cortical thickness, and cortical surface area between the two groups. Specifically, compared with HCs, patients with NDPH showed a significant decrease in cortical thickness of the left rostral cortex in the middle frontal gyrus, decreased cortical surface area of the left fusiform gyrus, decreased grey matter volume of the left superior frontal gyrus and the left middle frontal gyrus, and increased grey matter volume of the left calcarine. Furthermore, the power of the whole brain, bilateral frontal lobes, and right temporal lobe in the NDPH group were higher than that in HCs in the ripple frequency band (80-200 Hz). Functional and structural analysis suggested that there were structural changes and abnormal high frequency cortical activity in both frontal and temporal lobes in patients with NDPH.ConclusionOur findings indicated that patients with NDPH have abnormalities in brain morphology, such as cortical area, cortical thickness, and grey matter volume, accompanied by abnormal cortical neural activity. Brain structural changes in the frontotemporal cortex and abnormalities in cortical ripple activity may be involved in the pathogenesis of NDPH.

A distributed and efficient population code of mixed selectivity neurons for flexible navigation decisions

Decision-making requires flexibility to rapidly switch one’s actions in response to sensory stimuli depending on information stored in memory. We identified cortical areas and neural activity patterns underlying this flexibility during virtual navigation, where mice switched navigation toward or away from a visual cue depending on its match to a remembered cue. Optogenetics screening identified V1, posterior parietal cortex (PPC), and retrosplenial cortex (RSC) as necessary for accurate decisions. Calcium imaging revealed neurons that can mediate rapid navigation switches by encoding a mixture of a current and remembered visual cue. These mixed selectivity neurons emerged through task learning and predicted the mouse’s choices by forming efficient population codes before correct, but not incorrect, choices. They were distributed across posterior cortex, even V1, and were densest in RSC and sparsest in PPC. We propose flexibility in navigation decisions arises from neurons that mix visual and memory information within a visual-parietal-retrosplenial network.

Physical exercise mediates a cortical FMRP–mTOR pathway to improve resilience against chronic stress in adolescent mice

Aerobic exercise effectively relieves anxiety disorders via modulating neurogenesis and neural activity. The molecular mechanism of exercise-mediated anxiolysis, however, remains incomplete. On a chronic restrain stress (CRS) model in adolescent mice, we showed that 14-day treadmill exercise profoundly maintained normal neural activity and axonal myelination in the medial prefrontal cortex (mPFC), in association with the prevention of anxiety-like behaviors. Further interrogation of molecular mechanisms revealed the activation of the mechanistic target of the rapamycin (mTOR) pathway within mPFC under exercise training. At the upstream of mTOR, exercise-mediated brain RNA methylation inhibited the expression of Fragile X mental retardation protein (FMRP) to activate the mTOR pathway. In summary, treadmill exercise modulates an FMRP–mTOR pathway to maintain cortical neural activity and axonal myelination, contributing to improved stress resilience. These results extended our understanding of the molecular substrate of exercise-mediated anxiolytic effect during adolescent period.

Alterations of Spontaneous Cortical and Subcortical Activity in Type 2 Diabetes Mellitus with and without Depression

Introduction: Type 2 diabetes mellitus (T2DM) patients with depression have a higher risk of complications and mortality than T2DM without depression. However, the exact neuropathophysiological mechanism remains unclear. Consequently, the current study aimed to investigate the alteration of cortical and subcortical spontaneous neural activity in T2DM patients with and without depression. Methods: The demographic data, clinical variables, neuropsychological tests, and functional and anatomical magnetic resonance imaging of depressed T2DM (n = 47) of non-depressed T2DM (n = 59) and healthy controls (n = 41) were collected and evaluated. The correlation analysis, stepwise multiple linear regression, and receiver operating characteristic curve were performed for further analysis. Results: Abnormal neural activities in the bilateral posterior cingulate cortex (PCC) and hippocampus were observed in depressed and non-depressed T2DM and the right putamen of the depressed T2DM. Interestingly, the subcortical degree centrality (DC) of the right hippocampus and putamen were higher in depressed than non-depressed T2DM. Furthermore, the cortical amplitude of low-frequency fluctuation (ALFF) in PCC, subcortical DC in the putamen of depressed T2DM, and hippocampus of non-depressed T2DM was correlated with cognitive scores. In contrast, the cortical fractional ALFF in PCC of non-depressed T2DM was correlated with depression scores. Conclusions: The abnormalities of spontaneous cortical activity in PCC and subcortical activity in the hippocampus might represent the neurobiological feature of cerebral dysfunction in T2DM. Notably, the altered subcortical activity in the right putamen might mainly associate with negative emotion in T2DM, which could be a promising biomarker for recognizing early cerebral dysfunction in depressed T2DM. This study provided a novel insight into the neuropathophysiological mechanism of brain dysfunction in T2DM with and without depression.

Distinct Excitatory and Inhibitory Bump Wandering in a Stochastic Neural Field.

Localized persistent cortical neural activity is a validated neural substrate of parametric working memory. Such activity "bumps" represent the continuous location of a cue over several seconds. Pyramidal (excitatory ()) and interneuronal (inhibitory ()) subpopulations exhibit tuned bumps of activity, linking neural dynamics to behavioral inaccuracies observed in memory recall. However, many bump attractor models collapse these subpopulations into a single joint /(lateral inhibitory) population and do not consider the role of interpopulation neural architecture and noise correlations. Both factors have a high potential to impinge upon the stochastic dynamics of these bumps, ultimately shaping behavioral response variance. In our study, we consider a neural field model with separate / populations and leverage asymptotic analysis to derive a nonlinear Langevin system describing / bump interactions. While the bump attracts the bump, the bump stabilizes but can also repel the bump, which can result in prolonged relaxation dynamics when both bumps are perturbed. Furthermore, the structure of noise correlations within and between subpopulations strongly shapes the variance in bump position. Surprisingly, higher interpopulation correlations reduce variance.

Cortico-Subthalamic Field Potentials Support Classification of the Natural Gait Cycle in Parkinson's Disease and Reveal Individualized Spectral Signatures.

The ability of humans to coordinate stereotyped, alternating movements between the two legs during bipedal walking is a complex motor behavior that requires precisely timed activities across multiple nodes of the supraspinal network. Understanding of the neural network dynamics that underlie natural walking in humans is limited. We investigated cortical and subthalamic neural activities during overground walking and evaluated spectral biomarkers to decode the gait cycle in three patients with Parkinson's disease without gait disturbances. Patients were implanted with chronic bilateral deep brain stimulation (DBS) leads in the subthalamic nucleus (STN) and electrocorticography paddles overlaying the primary motor and somatosensory cortices. Local field potentials were recorded from these areas while the participants performed overground walking and synchronized to external gait kinematic sensors. We found that the STN displays increased low-frequency (4-12 Hz) spectral power during the period before contralateral leg swing. Furthermore, STN shows increased theta frequency (4-8 Hz) coherence with the primary motor through the initiation and early phase of contralateral leg swing. Additional analysis revealed that each patient had specific frequency bands that could detect a significant difference between left and right initial leg swing. Our findings indicate that there are alternating spectral changes between the two hemispheres in accordance with the gait cycle. In addition, we identified patient-specific, gait-related biomarkers in both the STN and cortical areas at discrete frequency bands that may be used to drive adaptive DBS to improve gait dysfunction in patients with Parkinson's disease.