Seminars

Margaret Livingstone of Harvard Medical School presents in Princeton Neuroscience Institute's public seminar series. Livingstone's laboratory studies how visual recognition occurs in the primate brain using behavior, brain imaging, and electrophysiology.

Over the last 20 years, neuroimaging and electrophysiology techniques have become central to understanding the mechanisms that accompany loss and recovery of consciousness. Much of this research is performed in the context of healthy individuals with neurotypical brain dynamics. Yet, a true understanding of how consciousness emerges from the joint action of neurons has to account for how severely pathological brains, often showing phenotypes typical of unconsciousness, can nonetheless generate a subjective viewpoint. In this presentation, I will start from the context of Disorders of Consciousness and will discuss recent work aimed at finding generalizable signatures of consciousness that are reliable across a spectrum of brain electrophysiological phenotypes focusing in particular on the notion of edge-of-chaos criticality.

The cortex comprises many neuronal types, which can be distinguished by their transcriptomes: the sets of genes they express. Little is known about the in vivo activity of these cell types, particularly as regards the structure of their spike trains, which might provide clues to cortical circuit function. To address this question, we used Neuropixels electrodes to record layer 5 excitatory populations in mouse V1, then transcriptomically identified the recorded cell types. To do so, we performed a subsequent recording of the same cells using 2-photon (2p) calcium imaging, identifying neurons between the two recording modalities by fingerprinting their responses to a “zebra noise” stimulus and estimating the path of the electrode through the 2p stack with a probabilistic method. We then cut brain slices and performed in situ transcriptomics to localize ~300 genes using coppaFISH3d, a new open source method, and aligned the transcriptomic data to the 2p stack. Analysis of the data is ongoing, and suggests substantial differences in spike time coordination between ET and IT neurons, as well as between transcriptomic subtypes of both these excitatory types.

Comprehending speech under acoustically challenging conditions is an everyday task that we can often execute with ease. However, accomplishing this requires the engagement of cognitive resources, such as auditory attention and working memory. The mechanisms that contribute to the robustness of speech comprehension are of substantial interest in the context of hearing mild to moderate hearing impairment, in which affected individuals typically report specific difficulties in understanding speech in background noise. Although hearing aids can help to mitigate this, they do not represent a universal solution, thus, finding alternative interventions is necessary. Given that age-related hearing loss (“presbycusis”) is inevitable, developing new approaches is all the more important in the context of aging populations. Moreover, untreated hearing loss in middle age has been identified as the most significant potentially modifiable predictor of dementia in later life. I will present research that has used a multi-methodological approach (fMRI, EEG, MEG and non-invasive brain stimulation) to try to elucidate the mechanisms that comprise the cognitive “last mile” in speech acousticallychallenging speech comprehension and to find ways to enhance them.

This webinar will showcase new approaches for electrophysiological recordings using our silicon neural probes and surface arrays combined with diverse optical methods such as wide-field or 2-photon imaging, fiber photometry, and optogenetic perturbations in awake, behaving mice. Multi-modal recording of single units and local field potentials across cortex, hippocampus and thalamus alongside calcium activity via GCaMP6F in cortical neurons in triple-transgenic animals or in hippocampal astrocytes via viral transduction are brought to bear to reveal hitherto inaccessible and under-appreciated aspects of coordinated dynamics in the brain.

A core aspect of clinical epileptology revolves around relating epileptic field potentials to underlying neural sources (e.g. an “epileptogenic focus”). Yet still, how neural population activity relates to epileptic field potentials and ultimately clinical phenomenology, remains far from being understood. After a brief overview on this topic, this seminar will focus on unpublished work, with an emphasis on seizure-related focal spreading depression. The presented results will include hippocampal and neocortical chronic in vivo two-photon population imaging and local field potential recordings of epileptic micronetworks in mice, in the context of viral encephalitis or optogenetic stimulation. The findings are corroborated by invasive depth electrode recordings (macroelectrodes and BF microwires) in epilepsy patients during pre-surgical evaluation. The presented work carries general implications for clinical epileptology, and basic epilepsy research.

The ability to organise one's body for action without having to think about it is taken for granted, whether it is handwriting, typing on a smartphone or computer keyboard, tying a shoelace or playing the piano. When compromised, e.g. in stroke, neurodegenerative and developmental disorders, the individuals’ study, work and day-to-day living are impacted with high societal costs. Until recently, indirect methods such as invasive recordings in animal models, computer simulations, and behavioural markers during sequence execution have been used to study covert motor sequence planning in humans. In this talk, I will demonstrate how multivariate pattern analyses of non-invasive neurophysiological recordings (MEG/EEG), fMRI, and muscular recordings, combined with a new behavioural paradigm, can help us investigate the structure and dynamics of motor sequence control before and after movement execution. Across paradigms, participants learned to retrieve and produce sequences of finger presses from long-term memory. Our findings suggest that sequence planning involves parallel pre-ordering of serial elements of the upcoming sequence, rather than a preparation of a serial trajectory of activation states. Additionally, we observed that the human neocortex automatically reorganizes the order and timing of well-trained movement sequences retrieved from memory into lower and higher-level representations on a trial-by-trial basis. This echoes behavioural transfer across task contexts and flexibility in the final hundreds of milliseconds before movement execution. These findings strongly support a hierarchical and dynamic model of skilled sequence control across the peri-movement phase, which may have implications for clinical interventions.

Coordination between excitatory and inhibitory synapses (providing positive and negative signals respectively) is required to ensure proper information processing in the brain. Many brain disorders, especially neurodevelopental disorders, are rooted in a specific disturbance of this coordination. In my research group we use a combination of two-photon microscopy and electrophisiology to examine how inhibitory synapses are fromed and how this formation is coordinated with nearby excitatroy synapses.

Repetitive spatiotemporal patterns in resting-state brain activities have been widely observed in various species and regions, such as rat and cat visual cortices. Since they resemble the preceding brain activities during tasks, they are assumed to reflect past experiences embedded in neuronal circuits. Moreover, spatiotemporal patterns involving whole-brain activities may also reflect a process that integrates information distributed over the entire brain, such as motor and visual information. Therefore, revealing such patterns may elucidate how the information is integrated to generate consciousness. In this talk, I will introduce our proposed method to estimate repetitive spatiotemporal patterns from resting-state brain activity data and show the spatiotemporal patterns estimated from human resting-state magnetoencephalography (MEG) and electroencephalography (EEG) data. Our analyses suggest that the patterns involved whole-brain propagating activities that reflected a process to integrate the information distributed over frequencies and networks. I will also introduce our current attempt to reveal signal flows and their roles in the spatiotemporal patterns using a big dataset. - Takeda et al., Estimating repetitive spatiotemporal patterns from resting-state brain activity data. NeuroImage (2016); 133:251-65. - Takeda et al., Whole-brain propagating patterns in human resting-state brain activities. NeuroImage (2021); 245:118711.

The development of circuit-based therapeutics to treat neurological and neuropsychiatric diseases require detailed localization and understanding of electrophysiological signals in the human brain. Electrodes can record and stimulate circuits in many ways, and we often rely on non-invasive imaging methods to predict the location to implant electrodes. However, electrophysiological and imaging signals measure the underlying tissue in a fundamentally different manner. To integrate multimodal data and benefit from these complementary measurements, I will describe an approach that considers how different measurements integrate signals across the underlying tissue. I will show how this approach helps relate fMRI and intracranial EEG measurements and provides new insights into how electrical stimulation influences human brain networks.

The human middle temporal complex (hMT+) has a crucial biological relevance for the processing and detection of direction and speed of motion in visual stimuli. In both humans and monkeys, it has been extensively investigated in terms of its retinotopic properties and selectivity for direction of moving stimuli; however, only in recent years there has been an increasing interest in how neurons in MT encode the speed of motion. In this talk, I will explore the proposed mechanism of speed encoding questioning whether hMT+ neuronal populations encode the stimulus speed directly, or whether they separate motion into its spatial and temporal components. I will characterize how neuronal populations in hMT+ encode the speed of moving visual stimuli using electrocorticography ECoG and 7T fMRI. I will illustrate that the neuronal populations measured in hMT+ are not directly tuned to stimulus speed, but instead encode speed through separate and independent spatial and temporal frequency tuning. Finally, I will suggest that this mechanism may play a role in evaluating multisensory responses for visual, tactile and auditory stimuli in hMT+.

On Wednesday, October 26th, at noon ET / 6PM CET, we will host Kara Johnson, PhD, and Ludvic Zrinzo, MD PhD, for the inaugural session of our newly conceived talk series format entitled "Stimulating Brains". Kara A. Johnson, a postdoctoral fellow in Dr. Coralie de Hemptinne’s lab at the University of Florida, will present her work on “Combining imaging and neurophysiology in Parkinson’s disease”. Ludvic Zrinzo, Professor of functional neurosurgery and head of the University College London functional neurosurgery unit, will give us a glimpse at the “Person behind the science”, and give a talk on “Neurosurgery for mental disorders: challenging mindsets”. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!

How does our brain generate consciousness, that is, the subjective experience of what it is like to see face or hear a sound? Do we become aware of a stimulus during early sensory processing or only later when information is shared in a wide-spread fronto-parietal network? Neural correlates of consciousness are typically identified by comparing brain activity when a constant stimulus (e.g., a face) is perceived versus not perceived. However, in most previous experiments, conscious perception was systematically confounded with post-perceptual processes such as decision-making and report. In this talk, I will present recent EEG and fMRI studies dissociating neural correlates of consciousness and task-related processing in visual and auditory perception. Our results suggest that consciousness emerges during early sensory processing, while late, fronto-parietal activity is associated with post-perceptual processes rather than awareness. These findings challenge predominant theories of consciousness and highlight the importance of considering task relevance as a confound across different neuroscientific methods, experimental paradigms and sensory modalities.

The human middle temporal complex (hMT+) has a crucial biological relevance for the processing and detection of direction and speed of motion in visual stimuli. In both humans and monkeys, it has been extensively investigated in terms of its retinotopic properties and selectivity for direction of moving stimuli; however, only in recent years there has been an increasing interest in how neurons in MT encode the speed of motion. In this talk, I will explore the proposed mechanism of speed encoding questioning whether hMT+ neuronal populations encode the stimulus speed directly, or whether they separate motion into its spatial and temporal components. I will characterize how neuronal populations in hMT+ encode the speed of moving visual stimuli using electrocorticography ECoG and 7T fMRI. I will illustrate that the neuronal populations measured in hMT+ are not directly tuned to stimulus speed, but instead encode speed through separate and independent spatial and temporal frequency tuning. Finally, I will show that this mechanism plays a role in evaluating multisensory responses for visual, tactile and auditory motion stimuli in hMT+.

Neural computations occurring simultaneously in multiple cerebral cortical regions are critical for mediating behaviors. Progress has been made in understanding how neural activity in specific cortical regions contributes to behavior. However, there is a lack of tools that allow simultaneous monitoring and perturbing neural activity from multiple cortical regions. We have engineered a suite of technologies to enable easy, robust access to much of the dorsal cortex of mice for optical and electrophysiological recordings. First, I will describe microsurgery robots that can programmed to perform delicate microsurgical procedures such as large bilateral craniotomies across the cortex and skull thinning in a semi-automated fashion. Next, I will describe digitally designed, morphologically realistic, transparent polymer skulls that allow long-term (+300 days) optical access. These polymer skulls allow mesoscopic imaging, as well as cellular and subcellular resolution two-photon imaging of neural structures up to 600 µm deep. We next engineered a widefield, miniaturized, head-mounted fluorescence microscope that is compatible with transparent polymer skull preparations. With a field of view of 8 × 10 mm2 and weighing less than 4 g, the ‘mini-mScope’ can image most of the mouse dorsal cortex with resolutions ranging from 39 to 56 µm. We used the mini-mScope to record mesoscale calcium activity across the dorsal cortex during sensory-evoked stimuli, open field behaviors, social interactions and transitions from wakefulness to sleep.

We have been developing Brain-Computer Interface (BCI) using electrocorticography (ECoG) [1] , which is recorded by electrodes implanted on brain surface, and magnetoencephalography (MEG) [2] , which records the cortical activities non-invasively, for the clinical applications. The invasive BCI using ECoG has been applied for severely paralyzed patient to restore the communication and motor function. The non-invasive BCI using MEG has been applied as a neurofeedback tool to modulate some pathological neural activities to treat some neuropsychiatric disorders. Although these techniques have been developed for clinical application, BCI is also an important tool to investigate neural function. For example, motor BCI records some neural activities in a part of the motor cortex to generate some movements of external devices. Although our motor system consists of complex system including motor cortex, basal ganglia, cerebellum, spinal cord and muscles, the BCI affords us to simplify the motor system with exactly known inputs, outputs and the relation of them. We can investigate the motor system by manipulating the parameters in BCI system. Recently, we are developing some BCIs to visualize and manipulate our perception and mental imagery. Although these BCI has been developed for clinical application, the BCI will be useful to understand our neural system to generate the perception and imagery. In this talk, I will introduce our study of phantom limb pain [3] , that is controlled by MEG-BCI, and the development of a communication BCI using ECoG [4] , that enable the subject to visualize the contents of their mental imagery. And I would like to discuss how much we can control our cortical activities that represent our perception and mental imagery. These examples demonstrate that BCI is a promising tool to visualize and manipulate the perception and imagery and to understand our consciousness. References 1. Yanagisawa, T., Hirata, M., Saitoh, Y., Kishima, H., Matsushita, K., Goto, T., Fukuma, R., Yokoi, H., Kamitani, Y., and Yoshimine, T. (2012). Electrocorticographic control of a prosthetic arm in paralyzed patients. AnnNeurol 71, 353-361. 2. Yanagisawa, T., Fukuma, R., Seymour, B., Hosomi, K., Kishima, H., Shimizu, T., Yokoi, H., Hirata, M., Yoshimine, T., Kamitani, Y., et al. (2016). Induced sensorimotor brain plasticity controls pain in phantom limb patients. Nature communications 7, 13209. 3. Yanagisawa, T., Fukuma, R., Seymour, B., Tanaka, M., Hosomi, K., Yamashita, O., Kishima, H., Kamitani, Y., and Saitoh, Y. (2020). BCI training to move a virtual hand reduces phantom limb pain: A randomized crossover trial. Neurology 95, e417-e426. 4. Ryohei Fukuma, Takufumi Yanagisawa, Shinji Nishimoto, Hidenori Sugano, Kentaro Tamura, Shota Yamamoto, Yasushi Iimura, Yuya Fujita, Satoru Oshino, Naoki Tani, Naoko Koide-Majima, Yukiyasu Kamitani, Haruhiko Kishima (2022). Voluntary control of semantic neural representations by imagery with conflicting visual stimulation. arXiv arXiv:2112.01223.

The view of human brain function has drastically shifted over the last decade, owing to the observation that the majority of brain activity is intrinsic rather than driven by external stimuli or cognitive demands. Specifically, all brain regions continuously communicate in spatiotemporally organized patterns that constitute the functional connectome, with consequences for cognition and behavior. In this talk, I will argue that another shift is underway, driven by new insights from synergistic interrogation of the functional connectome using different acquisition methods. The human functional connectome is typically investigated with functional magnetic resonance imaging (fMRI) that relies on the indirect hemodynamic signal, thereby emphasizing very slow connectivity across brain regions. Conversely, more recent methodological advances demonstrate that fast connectivity within the whole-brain connectome can be studied with real-time methods such as electroencephalography (EEG). Our findings show that combining fMRI with scalp or intracranial EEG in humans, especially when recorded concurrently, paints a rich picture of neural communication across the connectome. Specifically, the connectome comprises both fast, oscillation-based connectivity observable with EEG, as well as extremely slow processes best captured by fMRI. While the fast and slow processes share an important degree of spatial organization, these processes unfold in a temporally independent manner. Our observations suggest that fMRI and EEG may be envisaged as capturing distinct aspects of functional connectivity, rather than intermodal measurements of the same phenomenon. Infraslow fluctuation-based and rapid oscillation-based connectivity of various frequency bands constitute multiple dynamic trajectories through a shared state space of discrete connectome configurations. The multitude of flexible trajectories may concurrently enable functional connectivity across multiple independent sets of distributed brain regions.

Executive functions refer to a collection of mental processes such as attention, planning and problem solving, supported by a frontoparietal distributed brain network. These functions are essential for everyday life. Specifically in the context of patients with brain tumours there is a need to preserve them in order to enable good quality of life for patients. During surgeries for the removal of a brain tumour, the aim is to remove as much as possible of the tumour and at the same time prevent damage to the areas around it to preserve function and enable good quality of life for patients. In many cases, functional mapping is conducted during an awake surgery in order to identify areas critical for certain functions and avoid their surgical resection. While mapping is routinely done for functions such as movement and language, mapping executive functions is more challenging. Despite growing recognition in the importance of these functions for patient well-being in recent years, only a handful of studies addressed their intraoperative mapping. In the talk, I will present our new approach for mapping executive function areas using electrocorticography during awake brain surgery. These results will be complemented by neuroimaging data from healthy volunteers, directed at reliably localizing executive function regions in individuals using fMRI. I will also discuss more broadly challenges ofß using neuroimaging for neurosurgical applications. We aim to advance cross-modality neuroimaging of cognitive function which is pivotal to patient-tailored surgical interventions, and will ultimately lead to improved clinical outcomes.

Information processing is energetically expensive. In the mammalian brain, it is unclear how information coding and energy usage are regulated during food scarcity. I addressed this in the visual cortex of awake mice using whole-cell recordings and two-photon imaging to monitor layer 2/3 neuronal activity and ATP usage. I found that food restriction reduced synaptic ATP usage by 29% through a decrease in AMPA receptor conductance. Neuronal excitability was nonetheless preserved by a compensatory increase in input resistance and a depolarized resting membrane potential. Consequently, neurons spiked at similar rates as controls, but spent less ATP on underlying excitatory currents. This energy-saving strategy had a cost since it amplified the variability of visually-evoked subthreshold responses, leading to a 32% broadening in orientation tuning and impaired fine visual discrimination. This reduction in coding precision was associated with reduced levels of the fat mass-regulated hormone leptin and was restored by exogenous leptin supplementation. These findings reveal novel mechanisms that dynamically regulate energy usage and coding precision in neocortex.