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BACKGROUND: This study aimed to evaluate the short-term efficacy of repetitive transcranial magnetic stimulation (rTMS) on the treatment of failed back surgery syndrome (FBSS). METHODS: In this prospective clinical trial study, 13 patients with FBSS were selected to undergo rTMS, including 5 sessions of stimulation of the primary motor cortex of 90 trains with a frequency of 10 Hz for 2 seconds and an intertrain interval of 20 seconds with a total pulse rate of 1800 per session. The time of each session was 30 minutes with an intensity of 80% of the motor threshold. The severity of pain before and after the intervention was measured by the short-form McGill Pain Questionnaire and visual analog scale (VAS). RESULTS: The mean of pain severity was 26.54 ± 6.78 and 14.92 ± 10.1 before and after rTMS, respectively. The severity of pain was significantly decreased after the intervention (p = 0.001). According to the McGill Pain Questionnaire, the severity of pain in the patients was decreased by 44.09 ± 27.32. The mean of the severity of pain according to VAS was 77.31 ± 16.66 before rTMS and 53.46 ± 22.49 after rTMS, which showed that pain intensity was significantly decreased after the intervention (p = 0.006). CONCLUSIONS: The use of rTMS of the primary motor cortex in patients who have undergone lumbosacral spine surgery and suffer from pain related to FBSS is associated with a significant reduction in the severity of pain. Because rTMS is a noninvasive treatment method, it can be used as a suitable treatment in these patients.
Subject(s)
Failed Back Surgery Syndrome , Motor Cortex , Humans , Transcranial Magnetic Stimulation/methods , Failed Back Surgery Syndrome/therapy , Failed Back Surgery Syndrome/etiology , Pain Management/methods , Pain Measurement , Treatment OutcomeABSTRACT
Sensory stimulation triggers synchronized bioelectrical activity in the brain across various frequencies. This study delves into network-level activities, specifically focusing on local field potentials as a neural signature of visual category representation. Specifically, we studied the role of different local field potential frequency oscillation bands in visual stimulus category representation by presenting images of faces and objects to three monkeys while recording local field potential from inferior temporal cortex. We found category selective local field potential responses mainly for animate, but not inanimate, objects. Notably, face-selective local field potential responses were evident across all tested frequency bands, manifesting in both enhanced (above mean baseline activity) and suppressed (below mean baseline activity) local field potential powers. We observed four different local field potential response profiles based on frequency bands and face selective excitatory and suppressive responses. Low-frequency local field potential bands (1-30 Hz) were more prodominstaly suppressed by face stimulation than the high-frequency (30-170 Hz) local field potential bands. Furthermore, the low-frequency local field potentials conveyed less face category informtion than the high-frequency local field potential in both enhansive and suppressive conditions. Furthermore, we observed a negative correlation between face/object d-prime values in all the tested local field potential frequency bands and the anterior-posterior position of the recording sites. In addition, the power of low-frequency local field potential systematically declined across inferior temporal anterior-posterior positions, whereas high-frequency local field potential did not exhibit such a pattern. In general, for most of the above-mentioned findings somewhat similar results were observed for body, but not, other stimulus categories. The observed findings suggest that a balance of face selective excitation and inhibition across time and cortical space shape face category selectivity in inferior temporal cortex.
Subject(s)
Brain , Temporal Lobe , Temporal Lobe/physiology , Torso , Photic Stimulation/methods , Pattern Recognition, Visual/physiology , Brain Mapping/methodsABSTRACT
PURPOSE: Cervical spondylotic myelopathy (CSM) is one of the most notable causes of spinal cord impairment among elderly people worldwide. Little is written about the influence of postoperative rehabilitation on recovery of function in patients with CSM. In this study, we assessed the combined effects of repetitive transcranial magnetic stimulation (rTMS) combined with physiotherapy and physiotherapy alone on motor and sensory improvement assessed after spinal cord decompression in patients with CSM. METHODS: This prospective study comprised 52 patients with CSM; they were divided into two randomized groups after spinal cord decompression. The first group (group Ι) includes 26 patients, received a combination of rTMS and physiotherapy. The second group (group ΙΙ) of 26 patients underwent only physiotherapy. The neurologic assessment measures, including American Spinal Cord Injury Association score, modified Japanese Orthopaedic Association score, Ashworth scale, and Nurick grade, were recorded before and after rehabilitation interventions for each patient. RESULTS: According to the neurologic assessment measures, physiotherapy with/without rTMS after surgical decompression corresponded to significant improvement of motor function (P < 0. 01) without significant restoration of sensory function (P > 0. 01). Recovery rates of motor function were significantly better in group Ι than in group ΙΙ (P < 0. 01). There was no significant difference between two groups with respect to age (P = 0.162) and sex (P = 1.00). CONCLUSIONS: Although physiotherapy with/without rTMS improves motor function recovery after CSM surgery, rTMS in combination with physiotherapy leads to a more rapid motor function recovery than physiotherapy alone.
ABSTRACT
Introduction: Parkinson's disease (PD) is a movement disorder characterized by the pathological beta band (15-30 Hz) neural oscillations within the basal ganglia (BG). It is shown that the suppression of abnormal beta oscillations is correlated with the improvement of PD motor symptoms, which is a goal of standard therapies including deep brain stimulation (DBS). To overcome the stimulation-induced side effects and inefficiencies of conventional DBS (cDBS) and to reduce the administered stimulation current, closed-loop adaptive DBS (aDBS) techniques were developed. In this method, the frequency and/or amplitude of stimulation are modulated based on various disease biomarkers. Methods: Here, by computational modeling of a cortico-BG-thalamic network in normal and PD conditions, we show that closed-loop aDBS of the subthalamic nucleus (STN) with amplitude modulation leads to a more effective suppression of pathological beta oscillations within the parkinsonian BG. Results: Our results show that beta band neural oscillations are restored to their normal range and the reliability of the response of the thalamic neurons to motor cortex commands is retained due to aDBS with amplitude modulation. Furthermore, notably less stimulation current is administered during aDBS compared with cDBS due to a closed-loop control of stimulation amplitude based on the STN local field potential (LFP) beta activity. Discussion: Efficient models of closed-loop stimulation may contribute to the clinical development of optimized aDBS techniques designed to reduce potential stimulation-induced side effects of cDBS in PD patients while leading to a better therapeutic outcome.
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Heating and ventilation air conditioning systems in hospitals (cleanroom HVAC systems) are used to control the transmission/spreading of airborne diseases such as COVID-19. Air exiting from these systems may contribute to the spreading of coronavirus droplets outside of hospitals. Some research studies indicate that the shortest time of survival of SARS-CoV-2 in aerosol form (as droplets in the air) is four hours and the virus becomes inactive above 60 °C air temperature. Therefore, SARS-CoV-2 droplets cannot exit from the exhaust duct if the temperature is above 60 °C. At the condenser, heat is dissipated in the form of hot air which could be utilized to warm the exhaust air. The objective of this paper is to establish a novel technique for eliminating SARS-CoV-2 from cleanroom HVAC systems using the recovered heat of exhaust air. This can eliminate SARS-CoV-2 and reduce the greenhouse effect.
ABSTRACT
Face-selective neurons in the inferior temporal (IT) cortex respond to faces by either increasing (ENH) or decreasing (SUP) their spiking activities compared with their baseline. Although nearly half of IT face neurons are selectively suppressed by face stimulation, their role in face representation is not clear. To address this issue, we recorded the spiking activities and local field potential (LFP) from IT cortex of three monkeys while they viewed a large set of visual stimuli. LFP high-gamma (HG-LFP) power indicated the presence of both ENH and SUP face-selective neural clusters in IT cortex. The magnitude of HG-LFP power of the recording sites was correlated with the magnitude of change in the evoked spiking activities of its constituent neurons for both ENH and SUP face clusters. Spatial distribution of the ENH and SUP face clusters suggests the presence of a complex and heterogeneous face hypercluster organization in IT cortex. Importantly, ENH neurons conveyed more face category and SUP neurons conveyed more face identity information at both the single-unit and neuronal population levels. Onset and peak of suppressive single-unit, neuronal population, and HG-LFP power activities lagged those of the ENH ones. These results demonstrate that IT neuronal code for face representation is optimized by increasing sparseness through selective suppression of a subset of face neurons. We suggest that IT cortex contains spatial clusters of both ENH and SUP face neurons with distinct specialized functional role in face representation.NEW & NOTEWORTHY Electrophysiological and imaging studies have suggested that face information is encoded by a network of clusters of enhancive face-selective neurons in the visual cortex of man and monkey. We show that nearly half of face-selective neurons are suppressed by face stimulation. The suppressive neurons form spatial clusters and convey more face identity information than the enhancive face neurons. Our results suggest the presence of two neuronal subsystems for coarse and fine face information processing.
Subject(s)
Facial Recognition , Neurons/physiology , Temporal Lobe/physiology , Animals , Evoked Potentials, Visual , Gamma Rhythm , Macaca mulatta , Male , Temporal Lobe/cytologyABSTRACT
This study investigated effects of rate reduction and emphatic stress cues on second formant (F2) trajectories and articulatory movements during diphthong production in 11 typically developing school-aged children. F2 extent increased in slow and emphatic stress conditions, and tongue and jaw displacement increased in the emphatic stress condition compared to habitual speech. Tongue displacement significantly predicted F2 extent across speaking conditions. Results suggest that slow rate and emphatic stress cues induce articulatory and acoustic changes in children that may enhance clarity of the acoustic signal. Potential clinical implications for improving speech in children with dysarthria are discussed.
Subject(s)
Speech Acoustics , Speech Intelligibility , Biomechanical Phenomena , Child , Dysarthria , Humans , Phonetics , Speech , Speech Production MeasurementABSTRACT
We measured the fast temporal dynamics of face processing simultaneously across the human temporal cortex (TC) using intracranial recordings in eight participants. We found sites with selective responses to faces clustered in the ventral TC, which responded increasingly strongly to marine animal, bird, mammal, and human faces. Both face-selective and face-active but non-selective sites showed a posterior to anterior gradient in response time and selectivity. A sparse model focusing on information from the human face-selective sites performed as well as, or better than, anatomically distributed models when discriminating faces from non-faces stimuli. Additionally, we identified the posterior fusiform site (pFUS) as causally the most relevant node for inducing distortion of conscious face processing by direct electrical stimulation. These findings support anatomically discrete but temporally distributed response profiles in the human brain and provide a new common ground for unifying the seemingly contradictory modular and distributed modes of face processing.
Subject(s)
Facial Recognition , Temporal Lobe/physiology , Adult , Aged , Brain Mapping , Electric Stimulation , Female , Humans , Male , Middle Aged , Pattern Recognition, Visual , Temporal Lobe/chemistry , Young AdultABSTRACT
Reliable prediction of epileptic seizures is of prime importance as it can drastically change the quality of life for patients. This study aims to propose a real-time low computational approach for the prediction of epileptic seizures and to present an efficient hardware implementation of this approach for portable prediction systems. Three levels of feature extraction are performed to characterize the pre-ictal activities of the EEG signal. In the first-level, the line length algorithm is applied to the pre-ictal region. The features obtained in the first-level are mathematically integrated to extract the second-level features and then the line lengths of the second-level features are calculated to obtain our third-level feature. The third-level information is compared with predefined threshold levels to make a decision on whether the extracted characteristics are relevant to a seizure occurrence or not. The validity of this algorithm was tested by EEG recordings in the CHB-MIT database (97 seizures, 834.224 h) for 19 epileptic patients. The results showed that the average sensitivity was 90.62%, the specificity was 88.34%, the accuracy was 88.76% with the average false prediction rate as low as 0.0046 h-1, and the average prediction time was 23.3 min. The low computational complexity is the superiority of the proposed approach, which provides a technologically simple but accurate way of predicting epileptic seizures and enables hardware implantable devices. Graphical abstract Proposed seizure prediction algorithm and its features.
Subject(s)
Diagnosis, Computer-Assisted/methods , Electroencephalography/methods , Seizures/diagnosis , Adolescent , Algorithms , Child , Child, Preschool , Female , Humans , Infant , Male , Sensitivity and Specificity , Signal Processing, Computer-Assisted , Young AdultABSTRACT
This study aims to develop a semi-automatic system for brain tumor segmentation in 3D MR images. For a given image, noise was corrected using SUSAN algorithm first. A specific region of interest (ROI) that contains tumor was identified and then the intensity non-uniformity in ROI was corrected via the histogram normalization and intensity scaling. Each voxel in ROI was presented using 22 features and then was categorized as tumor or non-tumor by a multiple-classifier system. T1- and T2-weighted images and fluid-attenuated inversion recovery (FLAIR) were examined. The system performance in terms of Dice index (DI), sensitivity (SE) and specificity (SP) was evaluated using 150 simulated and 30 real images from the BraTS 2012 database. The results showed that the presented system with an average DI > 0.85, SE > 0.90, and SP > 0.98 for simulated data and DI > 0.80, SE > 0.84, and SP > 0.98 for real data might be used for accurate extraction of the brain tumors. Moreover, this system is 6 times faster than a similar system that processes the whole image. In comparison with two state-of-the-art tumor segmentation methods, our system improved DI (e.g., by 0.31 for low-grade tumors) and outperformed these algorithms. Considering the costs of imaging procedures, tumor identification accuracy and computation times, the proposed system that augmented general pathological information about tumors and used only 4 features of FLAIR images can be suggested as a brain tumor segmentation system for clinical applications.
Subject(s)
Algorithms , Brain Neoplasms/diagnostic imaging , Image Interpretation, Computer-Assisted , Imaging, Three-Dimensional , Knowledge Bases , HumansABSTRACT
We investigated the neural correlates of pleasure induced by listening to highly pleasant and neutral musical excerpts using electroencephalography (EEG). Power spectrum analysis of EEG data showed a distinct gradual change in the power of low-frequency oscillations in response to highly pleasant, but not neutral, musical excerpts. Specifically, listening to highly pleasant music was associated with (i) relatively higher oscillatory activity in the theta band over the frontocentral (FC) area and in the alpha band over the parieto-occipital area, and (ii) a gradual increase in the oscillatory power over time. Correlation analysis between behavioral and electrophysiological data revealed that theta power over the FC electrodes was correlated with subjective assessment of pleasantness while listening to music. To study the link between attention and positive valence in our experiments, volunteers performed a delayed match-to-sample memory task while listening to the musical excerpts. The subjects' performances were significantly lower under highly pleasant conditions compared to neutral conditions. Listening to pleasant music requires higher degrees of attention, leading to the observed decline in memory performance. Gradual development of low-frequency oscillations in the frontal and posterior areas may be at least partly due to gradual recruitment of higher levels of attention over time in response to pleasurable music.
Subject(s)
Music/psychology , Pleasure/physiology , Acoustic Stimulation , Adult , Attention/physiology , Auditory Perception/physiology , Cerebral Cortex/physiology , Electroencephalography/methods , Emotions/physiology , Female , Humans , Male , Theta Rhythm/physiologyABSTRACT
OBJECTIVE: To report the establishment of a new center for deep brain stimulation (DBS) as a surgical treatment for Parkinson disease and the surgical outcomes, from 2014 to 2017 in Shiraz, Southern Iran. METHODS: A new treatment program was established in Shiraz through a multidisciplinary team in 2014. Thirty-four patients underwent implantation of subthalamic nucleus (STN) electrodes during the last 3 years. Twenty-five patients fulfilled the minimum 6-month follow-up criteria. The baseline Unified Parkinson Disease Rating Scale (UPDRS) was assessed 1 month before surgery in both off-medication and on-medication states by a movement disorder neurologist. To evaluate the outcomes, subscores of the UPDRS were assessed in all patients before surgery and at least 6 months after the operation. RESULTS: All 25 patients had advanced Parkinson disease categorized as stage 3 or 4 using the Hoehn and Yahr scale. STN DBS resulted in a dramatic improvement in motor function of most patients. A reduction in dopaminergic medication dosage (average 60% reduction) was observed. The mean improvement was 40% in UPDRS II and 67% in UPDRS III. No surgical or hardware complications were observed. Stimulation-related adverse effects, including increased falling and worsening of speech, occurred in a few patients after surgery. Most of the patients experienced weight gain after surgery. CONCLUSIONS: Bilateral STN DBS is a satisfactory and safe treatment for carefully selected patients with advanced Parkinson disease. According to the results, the procedure can be performed safely and with comparable results in developing countries around the world.
Subject(s)
Deep Brain Stimulation/methods , Parkinson Disease/therapy , Subthalamic Nucleus , Adolescent , Adult , Aged , Conscious Sedation/methods , Deep Brain Stimulation/instrumentation , Developing Countries , Female , Humans , Implantable Neurostimulators , Iran , Magnetic Resonance Imaging , Male , Middle Aged , Multimodal Imaging , Patient Selection , Postoperative Care , Preoperative Care , Retrospective Studies , Stereotaxic Techniques , Surgicenters/organization & administration , Tomography, X-Ray Computed , Treatment OutcomeABSTRACT
The representation of visual objects in primate brain is distributed and multiple neurons are involved in encoding each object. One way to understand the neural basis of object representation is to estimate the number of neural dimensions that are needed for veridical representation of object categories. In this study, the characteristics of the match between physical-shape and neural representational spaces in monkey inferior temporal (IT) cortex were evaluated. Specifically, we examined how the number of neural dimensions, stimulus behavioral saliency and stimulus category selectivity of neurons affected the correlation between shape and neural representational spaces in IT cortex. Single-unit recordings from monkey IT cortex revealed that there was a significant match between face space and its neural representation at lower neural dimensions, whereas the optimal match for the non-face objects was observed at higher neural dimensions. There was a statistically significant match between the face and neural spaces only in the face-selective neurons, whereas a significant match was observed for non-face objects in all neurons regardless of their category selectivity. Interestingly, the face neurons showed a higher match for the non-face objects than for the faces at higher neural dimensions. The optimal representation of face space in the responses of the face neurons was a low dimensional map that emerged early (~150 ms post-stimulus onset) and was followed by a high dimensional and relatively late (~300 ms) map for the non-face stimuli. These results support a multiplexing function for the face neurons in the representation of very similar shape spaces, but with different dimensionality and timing scales.
Subject(s)
Facial Recognition , Neurons/physiology , Temporal Lobe/physiology , Animals , Female , Humans , Macaca mulatta , Male , Temporal Lobe/cytologyABSTRACT
Recent advances in brain and cognitive science studies have revolutionized concepts in neural dynamics, regulating mechanisms, coding systems and information processing networks which govern our function and behavior. Hidden aspects of neurological and psychiatric diseases are being understood and hopes for their treatment are emerging. Although the two comprehensive mega-projects on brain mapping are in place in the United States and Europe; the proportion of science contributed by the developing countries should not be downsized. With the granted supports from the Cognitive Sciences and Technologies Council (CSTC), Iran can take its role in research on brain and cognition further. The idea of research and development in Cognitive Sciences and Technologies (CST) is being disseminated across the country by CSTC. Towards this goal, the first Shiraz interdisciplinary meeting on CST was held on 9 January 2014 in Namazi hospital, Shiraz. CST research priorities, infrastructure development, education and promotion were among the main topics discussed during this interactive meeting. The steering committee of the first CST meeting in Shiraz decided to frame future research works within the "Brain and Cognition Study Group-Shiraz" (BCSG-Shiraz). The study group comprises scientific leaders from various allied disciplines including neuroscience, neurosurgery, neurology, psychiatry, psychology, radiology, physiology, bioengineering, biophysics, applied physics and telecommunication. As the headquarter for CST in the southern Iran, BCSG-Shiraz is determined to advocate "brain and cognition" awareness, education and research in close collaboration with CSTC. Together with CSTC, Shiraz Neuroscience Research center (SNRC) will take the initiative to cross boundaries in interdisciplinary works and multi-centric research projects within the study group.
ABSTRACT
BACKGROUND: Conventional methods for spike train analysis are predominantly based on the rate function. Additionally, many experiments have utilized a temporal coding mechanism. Several techniques have been used for analyzing these two sources of information separately, but using both sources in a single framework remains a challenging problem. Here, an innovative technique is proposed for spike train analysis that considers both rate and temporal information. METHODOLOGY/PRINCIPAL FINDINGS: Point process modeling approach is used to estimate the stimulus conditional distribution, based on observation of repeated trials. The extended Kalman filter is applied for estimation of the parameters in a parametric model. The marked point process strategy is used in order to extend this model from a single neuron to an entire neuronal population. Each spike train is transformed into a binary vector and then projected from the observation space onto the likelihood space. This projection generates a newly structured space that integrates temporal and rate information, thus improving performance of distribution-based classifiers. In this space, the stimulus-specific information is used as a distance metric between two stimuli. To illustrate the advantages of the proposed technique, spiking activity of inferior temporal cortex neurons in the macaque monkey are analyzed in both the observation and likelihood spaces. Based on goodness-of-fit, performance of the estimation method is demonstrated and the results are subsequently compared with the firing rate-based framework. CONCLUSIONS/SIGNIFICANCE: From both rate and temporal information integration and improvement in the neural discrimination of stimuli, it may be concluded that the likelihood space generates a more accurate representation of stimulus space. Further, an understanding of the neuronal mechanism devoted to visual object categorization may be addressed in this framework as well.