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New York University is seeking exceptional PhD candidates with strong quantitative training (e.g., physics, mathematics, engineering) coupled with a clear interest in scientific study of the brain. Doctoral programs are flexible, allowing students to pursue research across departmental boundaries. Admissions are handled separately by each department, and students interested in pursuing graduate studies should submit an application to the program that best fits their goals and interests.

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New York University is seeking exceptional PhD candidates with strong quantitative training (e.g., physics, mathematics, engineering) coupled with a clear interest in scientific study of the brain. Doctoral programs are flexible, allowing students to pursue research across departmental boundaries. Admissions are handled separately by each department, and students interested in pursuing graduate studies should submit an application to the program that best fits their goals and interests.

Computational Mechanisms of Predictive Processing in Brains and Machines

Predictive processing offers a unifying view of neural computation, proposing that brains continuously anticipate sensory input and update internal models based on prediction errors. In this talk, I will present converging evidence for the computational mechanisms underlying this framework across human neuroscience and deep neural networks. I will begin with recent work showing that large-scale distributed prediction-error encoding in the human brain directly predicts how sensory representations reorganize through predictive learning. I will then turn to PredNet, a popular predictive coding inspired deep network that has been widely used to model real-world biological vision systems. Using dynamic stimuli generated with our Spatiotemporal Style Transfer algorithm, we demonstrate that PredNet relies primarily on low-level spatiotemporal structure and remains insensitive to high-level content, revealing limits in its generalization capacity. Finally, I will discuss new recurrent vision models that integrate top-down feedback connections with intrinsic neural variability, uncovering a dual mechanism for robust sensory coding in which neural variability decorrelates unit responses, while top-down feedback stabilizes network dynamics. Together, these results outline how prediction error signaling and top-down feedback pathways shape adaptive sensory processing in biological and artificial systems.

Functional Imaging of the Human Brain: A Window into the Organization of the Human Mind

Vision for perception versus vision for action: dissociable contributions of visual sensory drives from primary visual cortex and superior colliculus neurons to orienting behaviors

The primary visual cortex (V1) directly projects to the superior colliculus (SC) and is believed to provide sensory drive for eye movements. Consistent with this, a majority of saccade-related SC neurons also exhibit short-latency, stimulus-driven visual responses, which are additionally feature-tuned. However, direct neurophysiological comparisons of the visual response properties of the two anatomically-connected brain areas are surprisingly lacking, especially with respect to active looking behaviors. I will describe a series of experiments characterizing visual response properties in primate V1 and SC neurons, exploring feature dimensions like visual field location, spatial frequency, orientation, contrast, and luminance polarity. The results suggest a substantial, qualitative reformatting of SC visual responses when compared to V1. For example, SC visual response latencies are actively delayed, independent of individual neuron tuning preferences, as a function of increasing spatial frequency, and this phenomenon is directly correlated with saccadic reaction times. Such “coarse-to-fine” rank ordering of SC visual response latencies as a function of spatial frequency is much weaker in V1, suggesting a dissociation of V1 responses from saccade timing. Consistent with this, when we next explored trial-by-trial correlations of individual neurons’ visual response strengths and visual response latencies with saccadic reaction times, we found that most SC neurons exhibited, on a trial-by-trial basis, stronger and earlier visual responses for faster saccadic reaction times. Moreover, these correlations were substantially higher for visual-motor neurons in the intermediate and deep layers than for more superficial visual-only neurons. No such correlations existed systematically in V1. Thus, visual responses in SC and V1 serve fundamentally different roles in active vision: V1 jumpstarts sensing and image analysis, but SC jumpstarts moving. I will finish by demonstrating, using V1 reversible inactivation, that, despite reformatting of signals from V1 to the brainstem, V1 is still a necessary gateway for visually-driven oculomotor responses to occur, even for the most reflexive of eye movement phenomena. This is a fundamental difference from rodent studies demonstrating clear V1-independent processing in afferent visual pathways bypassing the geniculostriate one, and it demonstrates the importance of multi-species comparisons in the study of oculomotor control.

Sensory tuning in neuronal movement commands

Inducing short to medium neuroplastic effects with Transcranial Ultrasound Stimulation

Sound waves can be used to modify brain activity safely and transiently with unprecedented precision even deep in the brain - unlike traditional brain stimulation methods. In a series of studies in humans and non-human primates, I will show that Transcranial Ultrasound Stimulation (TUS) can have medium- to long-lasting effects. Multiple read-outs allow us to conclude that TUS can perturb neuronal tissues up to 2h after intervention, including changes in local and distributed brain network configurations, behavioural changes, task-related neuronal changes and chemical changes in the sonicated focal volume. Combined with multiple neuroimaging techniques (resting state functional Magnetic Resonance Imaging [rsfMRI], Spectroscopy [MRS] and task-related fMRI changes), this talk will focus on recent human TUS studies.

Microstructural Features of the Human Sensorimotor Cortex in Health and Disease

Translation at the Synapse

Translation at the Synapse

The complex morphology of neurons, with synapses located hundreds of microns from the cell body, necessitates the localization of important cell biological machines, including ribosomes, within dendrites and axons. Local translation of mRNAs is important for the function and plasticity of synapses. Using advanced sequencing and imaging techniques we have updated our understanding of the local transcriptome and identified the local translatome- identifying over 800 transcripts for which local translation is the dominant source of protein. In addition, we have explored the unique mechanisms neurons use to meet protein demands at synapses, identifying surprising features of neuronal and synaptic protein synthesis.

The dynamic and plasticity of adaptive and homeostatic cortical myelination

Astroglial modulation of the antidepressant action of deep brain and bright light stimulation

Even if major depression is now the most common of psychiatric disorders, successful antidepressant treatments are still difficult to achieve. Therefore, a better understanding of the mechanisms of action of current antidepressant treatments is needed to ultimately identify new targets and enhance beneficial effects. Given the intimate relationships between astrocytes and neurons at synapses and the ability of astrocytes to "sense" neuronal communication and release gliotransmitters, an attractive hypothesis is emerging stating that the effects of antidepressants on brain function could be, at least in part, modulated by direct influences of astrocytes on neuronal networks. We will present two preclinical studies revealing a permissive role of glia in the antidepressant response: i) Control of the antidepressant-like effects of rat prefrontal cortex Deep Brain Stimulation (DBS) by astroglia, ii) Modulation of antidepressant efficacy of Bright Light Stimulation (BLS) by lateral habenula astroglia. Therefore, it is proposed that an unaltered neuronal-glial system constitutes a major prerequisite to optimize antidepressant efficacy of DBS or BLS. Collectively, these results pave also the way to the development of safer and more effective antidepressant strategies.

Untitled Seminar

Brain circuit dynamics in Action and Sleep

Our group focuses on brain computation, physiology and evolution, with a particular focus on network dynamics, sleep (evolution and mechanistic underpinnings), cortical computation (through the study of ancestral cortices), and sensorimotor processing. This talk will describe our recent results on the remarkable camouflage behavior of cuttlefish (action) and on brain activity in REM and NonREM in lizards (sleep). Both topics will focus on aspects of circuit dynamics.

Brain circuit dynamics in Action and Sleep

Our group focuses on brain computation, physiology and evolution, with a particular focus on network dynamics, sleep (evolution and mechanistic underpinnings), cortical computation (through the study of ancestral cortices), and sensorimotor processing. This talk will describe our recent results on the remarkable camouflage behavior of cuttlefish (action) and on brain activity in REM and NonREM in lizards (sleep). Both topics will focus on aspects of circuit dynamics.

Molecular and cellular mechanisms controlling neural stem cell activity

Neural stem cells (NSCs) generate new neurons throughout life. We use imaging-, genome editing-, and transgenesis-based approaches as well as cellular models of human diseases using pluripotent embryonic cells to study the molecular and cellular framework of NSC biology in the developing and adult brain. Aim of our research is to understand how physiologic and disease-associated alterations of neurogenesis are translated into stem cell-associated plastic changes in the developing and adult brain on a molecular, cellular, and behavioral level.

Organization and Computation in Neural Circuits

The role of motion in localizing objects

Everything we see has a location. We know where things are before we know what they are. But how do we know where things are? Receptive fields in the visual system specify location but neural delays lead to serious errors whenever targets or eyes are moving. Motion may be the problem here but motion can also be the solution, correcting for the effects of delays and eye movements. To demonstrate this, I will present results from three motion illusions where perceived location differs radically from physical location. These help understand how and where position is coded. We first look at the effects of a target’s simple forward motion on its perceived location. Second, we look at perceived location of a target that has internal motion as well as forward motion. The two directions combine to produce an illusory path. This “double-drift” illusion strongly affects perceived position but, surprisingly, not eye movements or attention. Even more surprising, fMRI shows that the shifted percept does not emerge in the visual cortex but is seen instead in the frontal lobes. Finally, we report that a moving frame also shifts the perceived positions of dots flashed within it. Participants report the dot positions relative to the frame, as if the frame were not moving. These frame-induced position effects suggest a link to visual stability where we see a steady world despite massive displacements during saccades. These motion-based effects on perceived location lead to new insights concerning how and where position is coded in the brain.

Mechanisms and precision therapies in genetic epilepsies

Large scale genetic studies and associated functional investigations have tremendously augmented our knowledge about the mechanisms underlying epileptic seizures, and sometimes also accompanying developmental problems. Pharmacotherapy of the epilepsies is routinely guided by trial and error, since predictors for a response to specific antiepileptic drugs are largely missing. The recent advances in the field of genetic epilepsies now offer an increasing amount of either well fitting established or new re-purposing therapies for genetic epilepsy syndromes based on understanding of the pathophysiological principles. Examples are provided by variants in ion channel or transporter encoding genes which cause a broad spectrum of epilepsy syndromes of variable severity and onset, (1) the ketogenic diet for glucose transporter defects of the blood-brain barrier, (2) Na+ channel blockers (e.g. carbamazepine) for gain-of-function Na+ channel mutations and avoidance of those drugs for loss-of-function mutations, and (3) specific K+ channel blockers for mutations with a gain-of-function defect in respective K+ channels. I will focus in my talk on the latter two including the underlying mechanisms, their relation to clinical phenotypes and possible therapeutic implications. In conclusion, genetic and mechanistic studies offer promising tools to predict therapeutic effects in rare epilepsies.

Using extra-hippocampal cognitive maps for goal-directed spatial navigation

Goal-directed navigation requires precise estimates of spatial relationships between current position and future goal, as well as planning of an associated route or action. While neurons in the hippocampal formation can represent the animal’s position and nearby trajectories, their role in determining the animal’s destination or action has been questioned. We thus hypothesize that brain regions outside the hippocampal formation may play complementary roles in navigation, particularly for guiding goal-directed behaviours based on the brain’s internal cognitive map. In this seminar, I will first describe a subpopulation of neurons in the retrosplenial cortex (RSC) that increase their firing when the animal approaches environmental boundaries, such as walls or edges. This boundary coding is independent of direct visual or tactile sensation but instead depends on inputs from the medial entorhinal cortex (MEC) that contains spatial tuning cells, such as grid cells or border cells. However, unlike MEC border cells, we found that RSC border cells encode environmental boundaries in a self-centred egocentric coordinate frame, which may allow an animal for efficient avoidance from approaching walls or edges during navigation. I will then discuss whether the brain can possess a precise estimate of remote target location during active environmental exploration. Such a spatial code has not been described in the hippocampal formation. However, we found that neurons in the rat orbitofrontal cortex (OFC) form spatial representations that persistently point to the animal’s subsequent goal destination throughout navigation. This destination coding emerges before navigation onset without direct sensory access to a distal goal, and are maintained via destination-specific neural ensemble dynamics. These findings together suggest key roles for extra-hippocampal regions in spatial navigation, enabling animals to choose appropriate actions toward a desired destination by avoiding possible dangers.

Brain dynamics related to short-term memory and learning

Innate immune response in brain pathologies: Lost in translation?

Inflammation is a key component of the innate immune response. Primarily designed to remove noxious agents and limit their detrimental effects, the prolonged and/or inappropriately scaled innate immune response may be detrimental to the host and lead to a chronic disease. Indeed, there is increasing evidence suggesting that a chronic deregulation of immunity may represent one of the key elements in the pathobiology of many brain disorders. Microglia are the principal immune cells of the brain. The consensus today is that once activated microglia/macrophages can acquire a wide repertoire of profiles ranging from the classical pro-inflammatory to alternative and protective phenotypes. Recently, we described a novel ribosome-based regulatory mechanism/checkpoint that controls innate immune gene translation and microglial activation involving RNA binding protein SRSF3. Here we will discuss the implications of SRSF3 and other endogenous immune regulators in deregulation of immunity observed in different models of brain pathologies. Furthermore, we will discuss whether targeting SRSF3 and mRNA translation may open novel avenues for therapeutic modulation of immune response in the brain.

A theory for Hebbian learning in recurrent E-I networks

The Stabilized Supralinear Network is a model of recurrently connected excitatory (E) and inhibitory (I) neurons with a supralinear input-output relation. It can explain cortical computations such as response normalization and inhibitory stabilization. However, the network's connectivity is designed by hand, based on experimental measurements. How the recurrent synaptic weights can be learned from the sensory input statistics in a biologically plausible way is unknown. Earlier theoretical work on plasticity focused on single neurons and the balance of excitation and inhibition but did not consider the simultaneous plasticity of recurrent synapses and the formation of receptive fields. Here we present a recurrent E-I network model where all synaptic connections are simultaneously plastic, and E neurons self-stabilize by recruiting co-tuned inhibition. Motivated by experimental results, we employ a local Hebbian plasticity rule with multiplicative normalization for E and I synapses. We develop a theoretical framework that explains how plasticity enables inhibition balanced excitatory receptive fields that match experimental results. We show analytically that sufficiently strong inhibition allows neurons' receptive fields to decorrelate and distribute themselves across the stimulus space. For strong recurrent excitation, the network becomes stabilized by inhibition, which prevents unconstrained self-excitation. In this regime, external inputs integrate sublinearly. As in the Stabilized Supralinear Network, this results in response normalization and winner-takes-all dynamics: when two competing stimuli are presented, the network response is dominated by the stronger stimulus while the weaker stimulus is suppressed. In summary, we present a biologically plausible theoretical framework to model plasticity in fully plastic recurrent E-I networks. While the connectivity is derived from the sensory input statistics, the circuit performs meaningful computations. Our work provides a mathematical framework of plasticity in recurrent networks, which has previously only been studied numerically and can serve as the basis for a new generation of brain-inspired unsupervised machine learning algorithms.

Molecular and functional heterogeneity of neural stem cells

New Strategies and Approaches to Tackle and Understand Neurological Disorder

Broadly, the Mauro Costa-Mattioli laboratory (The MCM Lab) encompasses two complementary lines of research. The first one, more traditional but very important, aims at unraveling the molecular mechanisms underlying memory formation (e.g., using state-of-the-art molecular and cell-specific genetic approaches). Learning and memory disorders can strike the brain during development (e.g., Autism Spectrum Disorders and Down Syndrome), as well as during adulthood (e.g., Alzheimer’s disease). We are interested in understanding the specific circuits and molecular pathways that are primarily targeted in these disorders and how they can be restored. To tackle these questions, we use a multidisciplinary, convergent and cross-species approach that combines mouse and fly genetics, molecular biology, electrophysiology, stem cell biology, optogenetics and behavioral techniques. The second line of research, more recent and relatively unexplored, is focused on understanding how gut microbes control CNS driven-behavior and brain function. Our recent discoveries, that microbes in the gut could modulate brain function and behavior in a very powerful way, have added a whole new dimension to the classic view of how complex behaviors are controlled. The unexpected findings have opened new avenues of study for us and are currently driving my lab to answer a host of new and very interesting questions: - What are the gut microbes (and metabolites) that regulate CNS-driven behaviors? Would it be possible to develop an unbiased screening method to identify specific microbes that regulate different behaviors? - If this is the case, can we identify how members of the gut microbiome (and their metabolites) mechanistically influence brain function? - What is the communication channel between the gut microbiota and the brain? Do different gut microbes use different ways to interact with the brain? - Could disruption of the gut microbial ecology cause neurodevelopmental dysfunction? If so, what is the impact of disruption in young and adult animals? - More importantly, could specific restoration of selected bacterial strains (new generation probiotics) represent a novel therapeutic approach for the targeted treatment of neurodevelopmental disorders? - Finally, can we develop microbiota-directed therapeutic foods to repair brain dysfunction in a variety of neurological disorders?

ALBA webinar on Diversity in brain research in East & South-East Asia: a gender perspective

As part of its webinar series on region-specific diversity issues, the ALBA Network is holding a panel discussion on gender issues in South-East Asia. This webinar wishes to highlight the various issues linked to gender in brain science in the major countries in the region, but also to discuss possible paths to equity.

Local tactile coding

The emergence of contrast invariance in cortical circuits

Neurons in the primary visual cortex (V1) encode the orientation and contrast of visual stimuli through changes in firing rate (Hubel and Wiesel, 1962). Their activity typically peaks at a preferred orientation and decays to zero at the orientations that are orthogonal to the preferred. This activity pattern is re-scaled by contrast but its shape is preserved, a phenomenon known as contrast invariance. Contrast-invariant selectivity is also observed at the population level in V1 (Carandini and Sengpiel, 2004). The mechanisms supporting the emergence of contrast-invariance at the population level remain unclear. How does the activity of different neurons with diverse orientation selectivity and non-linear contrast sensitivity combine to give rise to contrast-invariant population selectivity? Theoretical studies have shown that in the balance limit, the properties of single-neurons do not determine the population activity (van Vreeswijk and Sompolinsky, 1996). Instead, the synaptic dynamics (Mongillo et al., 2012) as well as the intracortical connectivity (Rosenbaum and Doiron, 2014) shape the population activity in balanced networks. We report that short-term plasticity can change the synaptic strength between neurons as a function of the presynaptic activity, which in turns modifies the population response to a stimulus. Thus, the same circuit can process a stimulus in different ways –linearly, sublinearly, supralinearly – depending on the properties of the synapses. We found that balanced networks with excitatory to excitatory short-term synaptic plasticity cannot be contrast-invariant. Instead, short-term plasticity modifies the network selectivity such that the tuning curves are narrower (broader) for increasing contrast if synapses are facilitating (depressing). Based on these results, we wondered whether balanced networks with plastic synapses (other than short-term) can support the emergence of contrast-invariant selectivity. Mathematically, we found that the only synaptic transformation that supports perfect contrast invariance in balanced networks is a power-law release of neurotransmitter as a function of the presynaptic firing rate (in the excitatory to excitatory and in the excitatory to inhibitory neurons). We validate this finding using spiking network simulations, where we report contrast-invariant tuning curves when synapses release the neurotransmitter following a power- law function of the presynaptic firing rate. In summary, we show that synaptic plasticity controls the type of non-linear network response to stimulus contrast and that it can be a potential mechanism mediating the emergence of contrast invariance in balanced networks with orientation-dependent connectivity. Our results therefore connect the physiology of individual synapses to the network level and may help understand the establishment of contrast-invariant selectivity.

Protein Synthesis at Neuronal Synapses

The complex morphology of neurons, with synapses located 100’s of microns from the cell body, necessitates the localization of important cell biological machines and processes within dendrites and axons. Using expansion microscopy together with metabolic labeling we have discovered that both postsynaptic spines and presynaptic terminals exhibit rapid translation, which exhibits differential sensitivity to different neurotransmitters and neuromodulators. In addition, we have explored the unique mechanisms neurons use to meet protein demands at synapses, identifying the transcriptome and translatome in the neuropil.

Local and global organization of synaptic inputs on cortical dendrites

Synaptic inputs on cortical dendrites are organized with remarkable subcellular precision at the micron level. This organization emerges during early postnatal development through patterned spontaneous activity and manifests both locally where synapses with similar functional properties are clustered, and globally along the axis from dendrite to soma. Recent experiments reveal species-specific differences in the local and global synaptic organization in mouse, ferret and macaque visual cortex. I will present a computational framework that implements functional and structural plasticity from spontaneous activity patterns to generate these different types of organization across species and scales. Within this framework, a single anatomical factor - the size of the visual cortex and the resulting magnification of visual space - can explain the observed differences. This allows us to make predictions about the organization of synapses also in other species and indicates that the proximal-distal axis of a dendrite might be central in endowing a neuron with powerful computational capabilities.

MidsummerBrains - computational neuroscience from my point of view

Computational neuroscience is a highly interdisciplinary field ranging from mathematics, physics and engineering to biology, medicine and psychology. Interdisciplinary collaborations have resulted in many groundbreaking innovations both in the research and application. The basis for successful collaborations is the ability to communicate across disciplines: What projects are the others working on? Which techniques and methods are they using? How is data collected, used and stored? In this webinar series, several experts describe their view on computational neuroscience in theory and application, and share experiences they had with interdisciplinary projects. This webinar is open for all interested students and researchers. If you are interested to participate live, please send a short message to smartstart@fz-juelich.de Please note, these lectures will be recorded for subsequent publishing as online lecture material.

Cerebral Cortex Connectomics

Densely mapping neuronal circuits at synaptic resolution is providing unprecedented insight into the formation and structure of the cerebral cortex. I’ll present recent advances and discuss what we can learn about precision, plasticity and possible patterns in mammalian neuronal circuits.

Dragons, Sleep, and the Claustrum

The mammalian claustrum, by virtue of its dense interconnectivity with cortex and other brain structures, has been hypothesized to mediate functions ranging from decision making to consciousness. I will be presenting experimental evidence for the existence of a claustrum in reptiles, its role in generating brain dynamics characteristic of sleep, and discuss our neuroetholgical approach towards understanding fundamental aspects of sleep and claustrum function.

Sleep, semantic memory, and creative problem solving

Creative thought relies on the reorganisation of existing knowledge. Sleep is known to be important for creative thinking, but there is a debate about which sleep stage is most relevant, and why. I will address this issue by proposing that Rapid Eye Movement sleep, or 'REM', and Non-REM sleep facilitate creativity in different ways. Memory replay mechanisms in Non-REM can abstract rules from corpuses of learned information, while replay in REM may promote novel associations. I propose that the iterative interleaving of REM and Non-REM across a night boosts the formation of complex knowledge frameworks, and allows these frameworks to be restructured - thus facilitating creative thought. My talk will discuss experiments exploring these hypotheses, and the mechanisms for these processes.

Comprehensive whole rat brain analysis: Expanding rat brain research with enhanced imaging and computational tools

FENS Forum 2024