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Low intensity rTMS: age dependent effects, and mechanisms underlying neural plasticity
Neuroplasticity is essential for the establishment and strengthening of neural circuits. Repetitive transcranial magnetic stimulation (rTMS) is commonly used to modulate cortical excitability and shows promise in the treatment of some neurological disorders. Low intensity magnetic stimulation (LI-rTMS), which does not directly elicit action potentials in the stimulated neurons, have also shown some therapeutic effects, and it is important to determine the biological mechanisms underlying the effects of these low intensity magnetic fields, such as would occur in the regions surrounding the central high-intensity focus of rTMS. Our team has used a focal low-intensity (10mT) magnetic stimulation approach to address some of these questions and to identify cellular mechanisms. I will present several studies from our laboratory, addressing (1) effects of LIrTMS on neuronal activity and excitability ; and (2) neuronal morphology and post-lesion repair. The ensemble of our results indicate that the effects of LI-rTMS depend upon the stimulation pattern, the age of the animal, and the presence of cellular magnetoreceptors.
Applied cognitive neuroscience to improve learning and therapeutics
Advancements in cognitive neuroscience have provided profound insights into the workings of the human brain and the methods used offer opportunities to enhance performance, cognition, and mental health. Drawing upon interdisciplinary collaborations in the University of California San Diego, Human Performance Optimization Lab, this talk explores the application of cognitive neuroscience principles in three domains to improve human performance and alleviate mental health challenges. The first section will discuss studies addressing the role of vision and oculomotor function in athletic performance and the potential to train these foundational abilities to improve performance and sports outcomes. The second domain considers the use of electrophysiological measurements of the brain and heart to detect, and possibly predict, errors in manual performance, as shown in a series of studies with surgeons as they perform robot-assisted surgery. Lastly, findings from clinical trials testing personalized interventional treatments for mood disorders will be discussed in which the temporal and spatial parameters of transcranial magnetic stimulation (TMS) are individualized to test if personalization improves treatment response and can be used as predictive biomarkers to guide treatment selection. Together, these translational studies use the measurement tools and constructs of cognitive neuroscience to improve human performance and well-being.
Evolution of convulsive therapy from electroconvulsive therapy to Magnetic Seizure Therapy; Interventional Neuropsychiatry
In April, we will host Nolan Williams and Mustafa Husain. Be prepared to embark on a journey from early brain stimulation with ECT to state-of-the art TMS protocols and magnetic seizure therapy! The talks will be held on Thursday, April 25th at noon ET / 6PM CET. Nolan Williams, MD, is an associate professor of Psychiatry and Behavioral Science at Stanford University. He developed the SAINT protocol, which is the first FDA-cleared non-invasive, rapid-acting neuromodulation treatment for treatment-resistant depression. Mustafa Husain, MD, is an adjunct professor of Psychiatry and Behavioral Sciences at Duke University and a professor of Psychiatry and Neurology at UT Southwestern Medical Center, Dallas. He will tell us about “Evolution of convulsive therapy from electroconvulsive therapy to Magnetic Seizure Therapy”. As always, we will also get a glimpse at the “Person behind the science”. Please register va talks.stimulatingbrains.org to receive the (free) Zoom link, subscribe to our newsletter, or follow us on Twitter/X for further updates!
Currents of Hope: how noninvasive brain stimulation is reshaping modern psychiatric care; Adapting to diversity: Integrating variability in brain structure and function into personalized / closed-loop non-invasive brain stimulation for substance use disorders
In March we will focus on TMS and host Ghazaleh Soleimani and Colleen Hanlon. The talks will talk place on Thursday, March 28th at noon ET – please be aware that this means 5PM CET since Boston already switched to summer time! Ghazaleh Soleimani, PhD, is a postdoctoral fellow in Dr Hamed Ekhtiari’s lab at the University of Minnesota. She is also the executive director of the International Network of tES/TMS for Addiction Medicine (INTAM). She will discuss “Adapting to diversity: Integrating variability in brain structure and function into personalized / closed-loop non-invasive brain stimulation for substance use disorders”. Colleen Hanlon, PhD, currently serves as a Vice President of Medical Affairs for BrainsWay, a company specializing in medical devices for mental health, including TMS. Colleen previously worked at the Medical University of South Carolina and Wake Forest School of Medicine. She received the International Brain Stimulation Early Career Award in 2023. She will discuss “Currents of Hope: how noninvasive brain stimulation is reshaping modern psychiatric care”. As always, we will also get a glimpse at the “Person behind the science”. Please register va talks.stimulatingbrains.org to receive the (free) Zoom link, subscribe to our newsletter, or follow us on Twitter/X for further updates!
Learning produces a hippocampal cognitive map in the form of an orthogonalized state machine
Cognitive maps confer animals with flexible intelligence by representing spatial, temporal, and abstract relationships that can be used to shape thought, planning, and behavior. Cognitive maps have been observed in the hippocampus, but their algorithmic form and the processes by which they are learned remain obscure. Here, we employed large-scale, longitudinal two-photon calcium imaging to record activity from thousands of neurons in the CA1 region of the hippocampus while mice learned to efficiently collect rewards from two subtly different versions of linear tracks in virtual reality. The results provide a detailed view of the formation of a cognitive map in the hippocampus. Throughout learning, both the animal behavior and hippocampal neural activity progressed through multiple intermediate stages, gradually revealing improved task representation that mirrored improved behavioral efficiency. The learning process led to progressive decorrelations in initially similar hippocampal neural activity within and across tracks, ultimately resulting in orthogonalized representations resembling a state machine capturing the inherent struture of the task. We show that a Hidden Markov Model (HMM) and a biologically plausible recurrent neural network trained using Hebbian learning can both capture core aspects of the learning dynamics and the orthogonalized representational structure in neural activity. In contrast, we show that gradient-based learning of sequence models such as Long Short-Term Memory networks (LSTMs) and Transformers do not naturally produce such orthogonalized representations. We further demonstrate that mice exhibited adaptive behavior in novel task settings, with neural activity reflecting flexible deployment of the state machine. These findings shed light on the mathematical form of cognitive maps, the learning rules that sculpt them, and the algorithms that promote adaptive behavior in animals. The work thus charts a course toward a deeper understanding of biological intelligence and offers insights toward developing more robust learning algorithms in artificial intelligence.
The Effects of Movement Parameters on Time Perception
Mobile organisms must be capable of deciding both where and when to move in order to keep up with a changing environment; therefore, a strong sense of time is necessary, otherwise, we would fail in many of our movement goals. Despite this intrinsic link between movement and timing, only recently has research begun to investigate the interaction. Two primary effects that have been observed include: movements biasing time estimates (i.e., affecting accuracy) as well as making time estimates more precise. The goal of this presentation is to review this literature, discuss a Bayesian cue combination framework to explain these effects, and discuss the experiments I have conducted to test the framework. The experiments herein include: a motor timing task comparing the effects of movement vs non-movement with and without feedback (Exp. 1A & 1B), a transcranial magnetic stimulation (TMS) study on the role of the supplementary motor area (SMA) in transforming temporal information (Exp. 2), and a perceptual timing task investigating the effect of noisy movement on time perception with both visual and auditory modalities (Exp. 3A & 3B). Together, the results of these studies support the Bayesian cue combination framework, in that: movement improves the precision of time perception not only in perceptual timing tasks but also motor timing tasks (Exp. 1A & 1B), stimulating the SMA appears to disrupt the transformation of temporal information (Exp. 2), and when movement becomes unreliable or noisy there is no longer an improvement in precision of time perception (Exp. 3A & 3B). Although there is support for the proposed framework, more studies (i.e., fMRI, TMS, EEG, etc.) need to be conducted in order to better understand where and how this may be instantiated in the brain; however, this work provides a starting point to better understanding the intrinsic connection between time and movement
Internal representation of musical rhythm: transformation from sound to periodic beat
When listening to music, humans readily perceive and move along with a periodic beat. Critically, perception of a periodic beat is commonly elicited by rhythmic stimuli with physical features arranged in a way that is not strictly periodic. Hence, beat perception must capitalize on mechanisms that transform stimulus features into a temporally recurrent format with emphasized beat periodicity. Here, I will present a line of work that aims to clarify the nature and neural basis of this transformation. In these studies, electrophysiological activity was recorded as participants listened to rhythms known to induce perception of a consistent beat across healthy Western adults. The results show that the human brain selectively emphasizes beat representation when it is not acoustically prominent in the stimulus, and this transformation (i) can be captured non-invasively using surface EEG in adult participants, (ii) is already in place in 5- to 6-month-old infants, and (iii) cannot be fully explained by subcortical auditory nonlinearities. Moreover, as revealed by human intracerebral recordings, a prominent beat representation emerges already in the primary auditory cortex. Finally, electrophysiological recordings from the auditory cortex of a rhesus monkey show a significant enhancement of beat periodicities in this area, similar to humans. Taken together, these findings indicate an early, general auditory cortical stage of processing by which rhythmic inputs are rendered more temporally recurrent than they are in reality. Already present in non-human primates and human infants, this "periodized" default format could then be shaped by higher-level associative sensory-motor areas and guide movement in individuals with strongly coupled auditory and motor systems. Together, this highlights the multiplicity of neural processes supporting coordinated musical behaviors widely observed across human cultures.The experiments herein include: a motor timing task comparing the effects of movement vs non-movement with and without feedback (Exp. 1A & 1B), a transcranial magnetic stimulation (TMS) study on the role of the supplementary motor area (SMA) in transforming temporal information (Exp. 2), and a perceptual timing task investigating the effect of noisy movement on time perception with both visual and auditory modalities (Exp. 3A & 3B). Together, the results of these studies support the Bayesian cue combination framework, in that: movement improves the precision of time perception not only in perceptual timing tasks but also motor timing tasks (Exp. 1A & 1B), stimulating the SMA appears to disrupt the transformation of temporal information (Exp. 2), and when movement becomes unreliable or noisy there is no longer an improvement in precision of time perception (Exp. 3A & 3B). Although there is support for the proposed framework, more studies (i.e., fMRI, TMS, EEG, etc.) need to be conducted in order to better understand where and how this may be instantiated in the brain; however, this work provides a starting point to better understanding the intrinsic connection between time and movement
Training Dynamic Spiking Neural Network via Forward Propagation Through Time
With recent advances in learning algorithms, recurrent networks of spiking neurons are achieving performance competitive with standard recurrent neural networks. Still, these learning algorithms are limited to small networks of simple spiking neurons and modest-length temporal sequences, as they impose high memory requirements, have difficulty training complex neuron models, and are incompatible with online learning.Taking inspiration from the concept of Liquid Time-Constant (LTCs), we introduce a novel class of spiking neurons, the Liquid Time-Constant Spiking Neuron (LTC-SN), resulting in functionality similar to the gating operation in LSTMs. We integrate these neurons in SNNs that are trained with FPTT and demonstrate that thus trained LTC-SNNs outperform various SNNs trained with BPTT on long sequences while enabling online learning and drastically reducing memory complexity. We show this for several classical benchmarks that can easily be varied in sequence length, like the Add Task and the DVS-gesture benchmark. We also show how FPTT-trained LTC-SNNs can be applied to large convolutional SNNs, where we demonstrate novel state-of-the-art for online learning in SNNs on a number of standard benchmarks (S-MNIST, R-MNIST, DVS-GESTURE) and also show that large feedforward SNNs can be trained successfully in an online manner to near (Fashion-MNIST, DVS-CIFAR10) or exceeding (PS-MNIST, R-MNIST) state-of-the-art performance as obtained with offline BPTT. Finally, the training and memory efficiency of FPTT enables us to directly train SNNs in an end-to-end manner at network sizes and complexity that was previously infeasible: we demonstrate this by training in an end-to-end fashion the first deep and performant spiking neural network for object localization and recognition. Taken together, we out contribution enable for the first time training large-scale complex spiking neural network architectures online and on long temporal sequences.
ISAM-NIG Webinars
Optimized Non-Invasive Brain Stimulation for Addiction Treatment
Multi-muscle TMS mapping assessment of the motor cortex reorganization after finger dexterity training
It is widely known that motor learning leads to reorganization changes in the motor cortex. Recently, we have shown that using navigated transcranial magnetic stimulation (TMS) allows us to reliably trace interactions among motor cortical representations (MCRs) of different upper limb muscles. Using this approach, we investigate changes in the MCRs after fine finger movement training. Our preliminary results demonstrated that areas of the APB and ADM and their overlaps tended to increase after finger independence training. Considering the behavioral data, hand dexterity increased for both hands, but the amplitudes of voluntary contraction of the muscles for the APB and ADM did not change significantly. The behavioral results correspond with a previously described suggestion that hand strength and hand dexterity are not directly related as well as an increase in overlaps between MCRs of the trained muscles supports the idea that voluntary muscle relaxation is an active physiological process.
The neural basis of flexible semantic cognition (BACN Mid-career Prize Lecture 2022)
Semantic cognition brings meaning to our world – it allows us to make sense of what we see and hear, and to produce adaptive thoughts and behaviour. Since we have a wealth of information about any given concept, our store of knowledge is not sufficient for successful semantic cognition; we also need mechanisms that can steer the information that we retrieve so it suits the context or our current goals. This talk traces the neural networks that underpin this flexibility in semantic cognition. It draws on evidence from multiple methods (neuropsychology, neuroimaging, neural stimulation) to show that two interacting heteromodal networks underpin different aspects of flexibility. Regions including anterior temporal cortex and left angular gyrus respond more strongly when semantic retrieval follows highly-related concepts or multiple convergent cues; the multivariate responses in these regions correspond to context-dependent aspects of meaning. A second network centred on left inferior frontal gyrus and left posterior middle temporal gyrus is associated with controlled semantic retrieval, responding more strongly when weak associations are required or there is more competition between concepts. This semantic control network is linked to creativity and also captures context-dependent aspects of meaning; however, this network specifically shows more similar multivariate responses across trials when association strength is weak, reflecting a common controlled retrieval state when more unusual associations are the focus. Evidence from neuropsychology, fMRI and TMS suggests that this semantic control network is distinct from multiple-demand cortex which supports executive control across domains, although challenging semantic tasks recruit both networks. The semantic control network is juxtaposed between regions of default mode network that might be sufficient for the retrieval of strong semantic relationships and multiple-demand regions in the left hemisphere, suggesting that the large-scale organisation of flexible semantic cognition can be understood in terms of cortical gradients that capture systematic functional transitions that are repeated in temporal, parietal and frontal cortex.
Towards the optimal protocol for investigation of the mirror neuron system
The study of mirror neurons (MN) has a long way since its discovery on monkeys and later on humans. However, in literature there are inconsistencies on the ways stimuli are presented and on the time of presentation. Which is the best way to present motor movement stimuli? Is it possible to estimate when the mirror neurons effect take place by using Transcranial Magnetic Stimulation at specific time windows? In the current study we test different ways of stimuli presentation (photo and video of hand movements) and brain stimulation (e.g. TMS) delivered on the dominant primary motor cortex (M1) at different time windows. Our aim is to solve this void still present on the field and create a standardized protocol that will generate the strongest mirror neurons response in order to have the way for future studies on the field.
The influence of menstrual cycle on the indices of cortical excitability
Menstruation is a normal physiological process in women occurring as a result of changes in two ovarian produced hormones – estrogen and progesterone. As a result of these fluctuations, women experience different symptoms in their bodies – their immune system changes (Sekigawa et al, 2004), there are changes in their cardiovascular and digestive system (Millikan, 2006), as well as skin (Hall and Phillips, 2005). But these hormone fluctuations produce major changes in their behavioral pattern as well causing: anxiety, sadness, heightened irritability and anger (Severino and Moline, 1995) which is usually classified as premenstrual syndrome (PMS). In some cases these symptoms severely impair women’s lives and professional help is required. The official diagnosis according to DSM-5 (2013) is premenstrual dysphoric disorder (PMDD). Despite its ubiquitous presence the origins of PMS and PMDD are poorly understood. Some efforts to understand the underlying brain state during the menstruation cycle were performed by using TMS (Smith et al, 1999; 2002; 2003; Inghilleri et al, 2004; Hausmann et al, 2006). But all of these experiments suffer from major shortcomings - no control groups and small number of subjects. Our plan is to address all of these shortcomings and make this the biggest (to our knowledge) experiment of its kind which will, hopefully, provide us with some much needed answers.
How inclusive and diverse is non-invasive brain stimulation in the treatment of psychiatric disorders?
How inclusive and diverse is non-invasive brain stimulation in the treatment of psychiatric disorders?Indira Tendolkar, Donders Institute for Brain, Cognition and Behavior, Department of Psychiatry. Mental illness is associated with a huge socioeconomic burden worldwide, with annual costs only in the Netherlands of €22 billion. Over two decades of cognitive and affective neuroscience research with modern tools of neuroimaging and neurophysiology in humans have given us a wealth of information about neural circuits underlying the main symptom domains of psychiatric disorders and their remediation. Neuromodulation entails the alteration of these neural circuits through invasive (e.g., DBS) or non-invasive (e.g., TMS) techniques with the aim of improving symptoms and/or functions and enhancing neuroplasticity. In my talk, I will focus on neuromodulation studies using repetitive transcranial magnetic stimulation (rTMS) as a relatively safe, noninvasive method, which can be performed simultaneously with neurocognitive interventions. Using the examples of two chronifying mental illnesses, namely obsessive compulsive disorders and major depressive disorder (MDD), I will review the concept of "state dependent" effects of rTMS and highlight how simultaneous or sequential cognitive interventions could help optimize rTMS therapy by providing further control of ongoing neural activity in targeted neural networks. Hardly any attention has been paid to diversity aspects in the studies. By including studies from low- and middle income countries, I will discuss the potential of non-invasive brain stimulation from a transcultural perspective.
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