Aura
aura
From aura to neuroinflammation: Has imaging resolved the puzzle of migraine pathophysiology?
In this talk I will present data from imaging studies that we have been conducting for the past 20 years trying to shed light on migraine physiopathology, from anatomical and functional MRI to positron emission tomography.
Migraine: a disorder of excitatory-inhibitory balance in multiple brain networks? Insights from genetic mouse models of the disease
Migraine is much more than an episodic headache. It is a complex brain disorder, characterized by a global dysfunction in multisensory information processing and integration. In a third of patients, the headache is preceded by transient sensory disturbances (aura), whose neurophysiological correlate is cortical spreading depression (CSD). The molecular, cellular and circuit mechanisms of the primary brain dysfunctions that underlie migraine onset, susceptibility to CSD and altered sensory processing remain largely unknown and are major open issues in the neurobiology of migraine. Genetic mouse models of a rare monogenic form of migraine with aura provide a unique experimental system to tackle these key unanswered questions. I will describe the functional alterations we have uncovered in the cerebral cortex of genetic mouse models and discuss the insights into the cellular and circuit mechanisms of migraine obtained from these findings.
Untitled Seminar
Laura Fenlon (Australia): Time shapes all brains: timing of a conserved transcriptional network underlies divergent cortical connectivity routes in mammalian brain development and evolution; Laurent Nguyen (Belgium): Regulation of cerebral cortex morphogenesis by migrating cells; Carol Ann Mason (USA): Wiring the eye to brain for binocular vision: lessons from the albino visual system. Thomas Perlmann (Sweden): Interrogating dopamine neuron development at the single cell level
Encoding and perceiving the texture of sounds: auditory midbrain codes for recognizing and categorizing auditory texture and for listening in noise
Natural soundscapes such as from a forest, a busy restaurant, or a busy intersection are generally composed of a cacophony of sounds that the brain needs to interpret either independently or collectively. In certain instances sounds - such as from moving cars, sirens, and people talking - are perceived in unison and are recognized collectively as single sound (e.g., city noise). In other instances, such as for the cocktail party problem, multiple sounds compete for attention so that the surrounding background noise (e.g., speech babble) interferes with the perception of a single sound source (e.g., a single talker). I will describe results from my lab on the perception and neural representation of auditory textures. Textures, such as a from a babbling brook, restaurant noise, or speech babble are stationary sounds consisting of multiple independent sound sources that can be quantitatively defined by summary statistics of an auditory model (McDermott & Simoncelli 2011). How and where in the auditory system are summary statistics represented and the neural codes that potentially contribute towards their perception, however, are largely unknown. Using high-density multi-channel recordings from the auditory midbrain of unanesthetized rabbits and complementary perceptual studies on human listeners, I will first describe neural and perceptual strategies for encoding and perceiving auditory textures. I will demonstrate how distinct statistics of sounds, including the sound spectrum and high-order statistics related to the temporal and spectral correlation structure of sounds, contribute to texture perception and are reflected in neural activity. Using decoding methods I will then demonstrate how various low and high-order neural response statistics can differentially contribute towards a variety of auditory tasks including texture recognition, discrimination, and categorization. Finally, I will show examples from our recent studies on how high-order sound statistics and accompanying neural activity underlie difficulties for recognizing speech in background noise.
Direction selectivity in hearing: monaural phase sensitivity in octopus neurons
The processing of temporal sound features is fundamental to hearing, and the auditory system displays a plethora of specializations, at many levels, to enable such processing. Octopus neurons are the most extreme temporally-specialized cells in the auditory (and perhaps entire) brain, which make them intriguing but also difficult to study. Notwithstanding the scant physiological data, these neurons have been a favorite cell type of modeling studies which have proposed that octopus cells have critical roles in pitch and speech perception. We used a range of in vivo recording and labeling methods to examine the hypothesis that tonotopic ordering of cochlear afferents combines with dendritic delays to compensate for cochlear delay - which would explain the highly entrained responses of octopus cells to sound transients. Unexpectedly, the experiments revealed that these neurons have marked selectivity to the direction of fast frequency glides, which is tied in a surprising way to intrinsic membrane properties and subthreshold events. The data suggest that octopus cells have a role in temporal comparisons across frequency and may play a role in auditory scene analysis.
40 years of headache research
Lifelong devotion to headache research has led to many discoveries. First a series of studies of brain blood flow during attacks of migraine. The results showed changes compatible with cortical spreading depression in migraine without aura effectively negating the then prevailing vasospastic/ischemic theory. In migraine without aura no changes in brain blood flow. This difference was crucial for the separation of migraine with aura and migraine without aura in the first and subsequent editions of the international headache classification headed by me. Then a human migraine provocation model that has elucidated the molecular mechanisms of migraine. Successively we showed in series of papers the importance of nitric oxide, histamine, CGRP, PACAP and prostanoids. Therapeutic effectiveness of antagonizing these provokers by tonabersat, L-NMMA, CGRP receptor antagonists and monoclonal antibodies and of NSAIDs. Present and future attempts to put all these signaling mechanisms into a framework but it is not easy
SCN1A/Nav1.1 sodium channel: loss and gain of function in epilepsy and migraine
Genetic mutations of the SCN1A gene, the voltage gated sodium channel NaV1.1, cause well-defined epilepsies, including the severe developmental and epileptic encephalopathy Dravet syndrome and genetic epilepsy with febrile seizures plus (GEFS+), as well as a severe form of migraine with aura, familial hemiplegic migraine (FHM). More recently, they have been identified in an extremely severe early infantile encephalopathy. Functional studies and animal models have contributed to disclose pathological mechanisms, which can be often linked to a straightforward loss- vs gain- of channel function. However, although this simple dichotomy is pertinent and useful, detailed pathological mechanisms in neuronal circuits can be more complex, sometimes because of unexpected homeostatic or pathologic responses. I will compare pathological mechanisms of epilepsy and migraine mutations studied with cellular, animal and computational models, highlighting a novel homeostatic response implemented by CCK-positive GABAergic neurons in a mouse model of Dravet syndrome, which may be boosted in therapeutic approaches.
Simons-Emory Workshop on Neural Dynamics: What could neural dynamics have to say about neural computation, and do we know how to listen?
Speakers will deliver focused 10-minute talks, with periods reserved for broader discussion on topics at the intersection of neural dynamics and computation. Organizer & Moderator: Chethan Pandarinath - Emory University and Georgia Tech Speakers & Discussants: Adrienne Fairhall - U Washington Mehrdad Jazayeri - MIT John Krakauer - John Hopkins Francesca Mastrogiuseppe - Gatsby / UCL Abigail Person - U Colorado Abigail Russo - Princeton Krishna Shenoy - Stanford Saurabh Vyas - Columbia
Rational thoughts in neural codes
First, we describe a new method for inferring the mental model of an animal performing a natural task. We use probabilistic methods to compute the most likely mental model based on an animal’s sensory observations and actions. This also reveals dynamic beliefs that would be optimal according to the animal’s internal model, and thus provides a practical notion of “rational thoughts.” Second, we construct a neural coding framework by which these rational thoughts, their computational dynamics, and actions can be identified within the manifold of neural activity. We illustrate the value of this approach by training an artificial neural network to perform a generalization of a widely used foraging task. We analyze the network’s behaviour to find rational thoughts, and successfully recover the neural properties that implemented those thoughts, providing a way of interpreting the complex neural dynamics of the artificial brain. Joint work with Zhengwei Wu, Minhae Kwon, Saurabh Daptardar, and Paul Schrater.
Does spatial hearing with bionic ears change with jittered binaural stimuli?
FENS Forum 2024
Sensitivity to envelope and pulse timing interaural time differences in prosthetic hearing
FENS Forum 2024
Sensitivity of inferior colliculus neurons to interaural time and level differences in adult neonatally deafened rats
FENS Forum 2024