Martin Vinck

Ernst Strüngmann Institut in Cooperation with Max Planck Society

Theories suggest that cognitive processes like attention have a rhythmic nature, however there is rising controversy surrounding the empirical findings supporting this theory. The controversy centers around the statistical methods employed by studies to test for rhythms in accuracy time courses (ATCs) around a behavioral event. To detect rhythms, p...

Recent studies in mice challenge the traditional notion of the V1 receptive field (RF) showing increases in V1 firing rates for stimuli presented in the surround, in the absence of a visual input into the classical RF. While this effect has been interpreted as a prediction of the occluded content or a prediction error, an alternative explanation is...

Recent studies in mice challenge the traditional notion of the V1 receptive field (RF) showing increases in V1 firing rates for stimuli presented in the surround, in the absence of a visual input into the classical RF. While this effect has been interpreted as a prediction of the occluded content or a prediction error, an alternative explanation is...

Recent studies in mice challenge the traditional notion of the V1 receptive field (RF) showing increases in V1 firing rates for stimuli presented in the surround, in the absence of a visual input into the classical RF. While this effect has been interpreted as a prediction of the occluded content or a prediction error, an alternative explanation is...

A relevant question concerning inter-areal communication in the cortex is whether these interactions are synergistic. Synergy refers to the complementary effect of multiple brain signals conveying more information than the sum of each isolated signal. Redundancy, on the other hand, refers to the common information shared between brain signals. Here...

Compressed hippocampal place-cell sequences have been associated with memory storage, retrieval and planning, but it remains unclear how they align with activity in the parahippocampal cortex. In a visuospatial discrimination task, we found a wide repertoire of hippocampal place cell sequences, which recapitulated paths across the task environment....

Anticipating future events is a key computational task for neuronal networks. Experimental evidence suggests that reliable temporal sequences in neural activity play a functional role in the association and anticipation of events in time. However, how neurons can differentiate and anticipate multiple spike sequences remains largely unknown. We impl...

Intelligent behavior depends on the brain’s ability to anticipate future events. However, the learning rules that enable neurons to predict and fire ahead of sensory inputs remain largely unknown. We propose a plasticity rule based on predictive processing, where the neuron learns a low-rank model of the synaptic input dynamics in its membrane pote...

What determines the aesthetic appeal of artworks? Recent work suggests that aesthetic appeal can, to some extent, be predicted from a visual artwork's image features. Yet a large fraction of variance in aesthetic ratings remains unexplained and may relate to individual preferences. We hypothesized that an artwork's aesthetic appeal depends strongly...

Convolutional neural networks (CNNs) are one of the most successful computer vision systems to solve object recognition. Furthermore, CNNs have major applications in understanding the nature of visual representations in the human brain. Yet it remains poorly understood how CNNs actually make their decisions, what the nature of their internal repres...

Neural coding and memory formation depend on temporal spiking sequences that span high-dimensional neural ensembles. The unsupervised discovery and characterization of these spiking sequences requires a suitable dissimilarity measure to spiking patterns, which can then be used for clustering and decoding. Here, we present a new dissimilarity measur...

Inter-areal coherence has been hypothesized as a mechanism for inter-areal communication. Indeed, empirical studies have observed an increase in inter-areal coherence with attention. Yet, the mechanisms underlying changes in coherence remain largely unknown. Both attention and stimulus salience are associated with shifts in the peak frequency of ga...

The traditional view on coding in the cortex is that populations of neurons primarily convey stimulus information through the spike count. However, given the speed of sensory processing, it has been hypothesized that sensory encoding may rely on the spike-timing relationships among neurons. Here, we use a recently developed method based on Optimal...

Rhythmic flicker stimulation has gained interest as a treatment for neurodegenerative diseases and as a method for frequency tagging neural activity. Yet, little is known about the way in which flicker-induced synchronization propagates across cortical levels and impacts different cell types. Here, we use Neuropixels to record from the lateral geni...

Cortical computations require coordination of neuronal activity within and across multiple areas. We characterized spiking relationships within and between areas by quantifying coupling of single neurons to population firing patterns. Single-neuron population coupling (SNPC) was investigated using ensemble recordings from hippocampal CA1 region and...

GABAergic inhibition plays an important role in the establishment and maintenance of cortical circuits during development. Neuregulin 1 (Nrg1) and its interneuron-specific receptor ErbB4 are key elements of a signaling pathway critical for the maturation and proper synaptic connectivity of interneurons. Using conditional deletions of the ERBB4 gene...

Cortical information processing is thought to be facilitated by the resonant properties of individual neurons and neuronal networks, which selectively amplify inputs at specific frequencies. We used optogenetics to test how different input frequencies are encoded by excitatory cells and parvalbumin-expressing (PV) interneurons in mouse V1. Spike ph...

Sensory processing relies on interactions between excitatory and inhibitory neurons, which are often coordinated by 30-80Hz gamma oscillations. However, the specific contributions of distinct interneurons to gamma synchronization remain unclear. We performed high-density recordings from V1 in awake mice and used optogenetics to identify PV+ (Parval...

What mechanisms underlie flexible inter-areal communication in the cortex? We consider four mechanisms for temporal coordination and their contributions to communication: (1) Oscillatory synchronization (communication-through-coherence); (2) communication-through-resonance; (3) non-linear integration; and (4) linear signal transmission (coherence-t...

Accurately measuring and quantifying the underlying interactions between brain areas is crucial for understanding the flow of information in the brain. Of particular interest in the field of electrophysiology is the analysis and characterization of the spectral properties of these interactions. Coherence and Granger-Geweke Causality are commonly us...

An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. convey information beyond what can be performed by isolated signals. Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To t...

Rhythmic flicker stimulation has gained interest as a treatment for neurodegenerative diseases and a method for frequency tagging neural activity in human EEG/MEG recordings. Yet, little is known about the way in which flicker-induced synchronization propagates across cortical levels and impacts different cell types. Here, we used Neuropixels to si...

Dimensionality reduction tools like t-SNE and UMAP are widely used for high-dimensional data analysis. For instance, these tools are applied in biology to describe spiking patterns of neuronal populations or the genetic profiles of different cell types. Here, we show that when data include noise points that are randomly scattered within a high-dime...

Convolutional neural networks (CNNs) are one of the most successful computer vision systems to solve object recognition. Furthermore, CNNs have major applications in understanding the nature of visual representations in the human brain. Yet it remains poorly understood how CNNs actually make their decisions, what the nature of their internal repres...

Attention gates the flow of sensory information across brain areas. Mechanistically, attention should depend on a modulation of both feedback (FB) and feedforward (FF) projections, which terminate in distinct laminar compartments and target specific neural populations. We performed simultaneous laminar recordings from macaque V1 and V4 and identifi...

Cortical areas are reciprocally coupled via feedforward (FF) and feedback (FB) connections that have distinct laminar profiles. Recurrent interactions between FF and FB streams may underlie context-dependent, flexible processing of sensory stimuli and the formation of predictions. Hierarchical predictive coding theories postulate that the communica...

Behavioral studies suggest attention-related performance fluctuates at a 3-8Hz rhythm (Landau and Fries, 2012; Fiebelkorn et al., 2013). Brookshire (2022) argues that these previous studies failed to distinguish periodic from aperiodic processes, which led to the spurious detection of rhythms. The argument is based on simulations of accuracy time c...

Circuits of excitatory and inhibitory neurons generate gamma-rhythmic activity (30–80 Hz). Gamma-cycles show spontaneous variability in amplitude and duration. To investigate the mechanisms underlying this variability, we recorded local-field-potentials (LFPs) and spikes from awake macaque V1. We developed a noise-robust method to detect gamma-cycl...

The influence of sensory experience on cortical feedforward and feedback interactions has rarely been studied in the auditory cortex. Previous work has documented a dystrophic effect of deafness in deep cortical layers, and a reduction of interareal couplings between primary and secondary auditory areas in congenital deafness which was particularly...

Predictive coding is an important candidate theory of self-supervised learning in the brain. Its central idea is that sensory responses result from comparisons between bottom-up inputs and contextual predictions, a process in which rates and synchronization may play distinct roles. We recorded from awake macaque V1 and developed a technique to quan...

When a visual stimulus is repeated, average neuronal responses typically decrease, yet they might maintain or even increase their impact through increased synchronization. Previous work has found that many repetitions of a grating lead to increasing gamma-band synchronization. Here, we show in awake macaque area V1 that both repetition-related redu...

Intelligent behavior depends on the brain’s ability to anticipate future events. However, the learning rules that enable neurons to predict and fire ahead of sensory inputs remain largely unknown. We propose a plasticity rule based on pre-dictive processing, where the neuron learns a low-rank model of the synaptic input dynamics in its membrane pot...

Neural coding and memory formation depend on temporal spiking sequences that span high-dimensional neural ensembles. The unsupervised discovery and characterization of these spiking sequences require a suitable dissimilarity measure to compare any two spiking patterns. Here, we present a new measure of dissimilarity between multi-neuron spike seque...

Cognitive functions are subserved by rhythmic neuronal synchronization across widely distributed brain areas. In 105 area pairs, we investigated functional connectivity (FC) through coherence, power correlation, and Granger causality (GC) in the theta, beta, high-beta, and gamma rhythms. Between rhythms, spatial FC patterns were largely independent...

Inter-areal coherence between field potentials is a widespread phenomenon in cortex. Coherence has been hypothesized to reflect phase-synchronization between oscillators and flexibly gate communication according to behavioral and cognitive demands. We reveal an alternative mechanism where coherence is not the cause but the consequence of communicat...

What determines the aesthetic appeal of artworks? Recent work suggests that aesthetic appeal can to some extent be predicted from a visual artwork’s image features. Yet, a large fraction of variance in aesthetic ratings remains unexplained and may relate to individual preferences. We hypothesized that an artwork’s aesthetic appeal depends strongly...

The function of the cerebral cortex essentially depends on the ability to form functional assemblies across different cortical areas serving different functions. Here we investigated how developmental hearing experience affects functional and effective interareal connectivity in the auditory cortex in an animal model with years-long and complete au...

Hierarchy is a major organizational principle of the cortex and underscores modern computational theories of cortical function. The local microcircuit amplifies long-distance inter-areal input, which show distance-dependent changes in their laminar profiles. Statistical modeling of these changes in laminar profiles demonstrates that inputs from mul...

What is the relationship between anatomical connection strength and rhythmic synchronization? Simultaneous recordings of 15 cortical areas in two macaque monkeys show that interareal networks are functionally organized in spatially distinct modules with specific synchronization frequencies, i.e. frequency-specific functional connectomes. We relate...

GABAergic inhibition plays an important role in the establishment and maintenance of cortical circuits during development. Neuregulin 1 (Nrg1) and its interneuron-specific receptor ErbB4 are key elements of a signaling pathway critical for the maturation and proper synaptic connectivity of interneurons. Using conditional deletions of the ERBB4 gene...

When a visual stimulus is repeated, average neuronal responses typically decrease, yet they might maintain or even increase their impact through increased synchronization. Previous work has found that many repetitions of a grating lead to increasing gamma-band synchronization. Here we show in awake macaque area V1 that both, repetition-related redu...

Feedforward deep neural networks for object recognition are a promising model of visual processing and can accurately predict firing-rate responses along the ventral stream. Yet, these networks have limitations as models of various aspects of cortical processing related to recurrent connectivity, including neuronal synchronization and the integrati...

What does neuronal coherence tell us about neuronal communication? Does coherence between field potentials (e.g. LFP, EEG, MEG) reflect spiking entrainment or coupling between oscillators? Is it a mechanism for communication between brain areas, or a byproduct of interareal connectivity? We hypothesized that interareal coherence is explained by the...

Neuronal coding and memory formation depend on temporal activation patterns spanning high-dimensional ensembles of neurons. To characterize these high-dimensional spike sequences, it is critical to measure their dissimilarity across different epochs (e.g. stimuli, brain states) in terms of all the relative spike-timing relationships. Such a dissimi...

Hierarchy is a major organizational principle of the cortex and underscores modern computational theories of cortical function. The local microcircuit amplifies long-distance inter-areal input, which show distance-dependent changes in their laminar profiles. Statistical modeling of these changes in laminar profiles demonstrates that inputs from mul...

Neurons in many brain regions exhibit spontaneous, intrinsic rhythmic firing activity. This rhythmic firing activity may determine the way in which these neurons respond to extrinsic synaptic inputs. We hypothesized that neurons should be most responsive to inputs at the frequency of the intrinsic oscillation frequency. We addressed this question i...

In addition to coding a subject’s location in space, the hippocampus has been suggested to code social information, including the spatial position of conspecifics. “Social place cells” have been reported for tasks in which an observer mimics the behavior of a demonstrator. We examine whether rat hippocampal neurons may encode the behavior of a mini...

Cortical computation depends on interactions between excitatory and inhibitory neurons. The contributions of distinct neuron types to sensory processing and network synchronization in primate visual cortex remain largely undetermined. We show that in awake monkey V1, there exists a distinct cell type (››30% of neurons) that has narrow-waveform (NW)...

Experts review the latest research on the neocortex and consider potential directions for future research. Over the past decade, technological advances have dramatically increased information on the structural and functional organization of the brain, especially the cerebral cortex. This explosion of data has radically expanded our ability to chara...

Communication among visual cortical areas depends on gamma oscillations. Respective gamma cycles vary substantially in amplitude and duration, yet it is unclear how those fundamental parameters relate to each other and to spiking activity. We recorded local-field-potentials (LFPs) and spiking activity from awake macaque area V1 and detected amplitu...

Micro Electrode Arrays were used to simultaneously record spontaneous extracellular action potentials from 10 to 30 dopamine neurons in acute brain slices from the lateral Ventral Tegmental Area (VTA) of the rat. The spike train of an individual neuron was used to characterize the firing pattern: firing rate, firing irregularity and oscillation fre...

The activity of the cerebral cortex patterns into recurring dynamic motifs. In the present issue of Neuron, Senzai et al. (2019) elucidate how these motifs recruit excitatory and inhibitory neurons across cortical layers and how brain state modulates laminar interactions.

The integration of direct bottom-up inputs with contextual information is a core feature of neocortical circuits. In area V1, neurons may reduce their firing rates when their receptive field input can be predicted by spatial context. Gamma-synchronized (30-80Hz) firing may provide a complementary signal to rates, reflecting stronger synchronization...

The integration of direct bottom-up inputs with contextual information is a core feature of neocortical circuits. In area V1, neurons may reduce their firing rates when their receptive field input can be predicted by spatial context. Gamma-synchronized (30-80Hz) firing may provide a complementary signal to rates, reflecting stronger synchronization...

Although failure of GABAergic inhibition is a commonly hypothesized mechanism underlying seizure disorders, the series of events that precipitate a rapid shift from healthy to ictal activity remain unclear. Furthermore, the diversity of inhibitory interneuron populations poses a challenge for understanding local circuit interactions during seizure...

Compared to wakefulness, neuronal activity during non-REM sleep is characterized by a decreased ability to integrate information, but also by the re-emergence of task-related information patterns. To investigate the mechanisms underlying these seemingly opposing phenomena, we measured directed information flow by computing transfer entropy between...

In this review, we explore how contextual modulations of sensory processing are implemented within the local cortical circuit. We focus on contextual influences of global arousal state (e.g. how alert am I?), sensory predictions (e.g. which stimuli do I expect?), and top-down attention (what is relevant to me?). We review recent literature suggesti...

Temporally ordered multi-neuron patterns likely encode information in the brain. We introduce an unsupervised method, SPOTDisClust (Spike Pattern Optimal Transport Dissimilarity Clustering), for their detection from high-dimensional neural ensembles. SPOTDisClust measures similarity between two ensemble spike patterns by determining the minimum tra...

HDBSCAN labels for each of the seven main figures. Shown are the excess of mass (EOM) and the leaf cluster selection methods of the HDBSCAN algorithm (see Methods). Grey points are identified as noise points by HDBSCAN, other colors correspond to clusters. (PDF)

Illustration of how the EMD is a noise-robust measure of distance for spikes. We consider four rate modulations (top left) each consisting of a single activation pulse and a baseline. We then generated spikes from the four rate modulations according to an inhomogeneous Poisson process (top right). The rate modulations may represent cross-correlatio...

Clustering performance for a case with precise spike sequences. Five patterns were defined by selecting for each pattern a random time point at which the neuron would fire a spike. In addition, we inserted a varying number of noise spikes per neuron according to a homogeneous Poisson process, and also varied the amount of temporal jitter in the pat...

Dependence of clustering performance on chosen window length and temporal jitter of spike pattern onset. The parameter settings for the patterns underlying this figure are equivalent to Fig 1. Each pattern has a length of 300 samples, and is embedded in a larger window starting from -300 samples to +300 samples, with homogeneous noise surrounding t...

Application to neuronal data of window length selection, matching Fig 8. We repeated the clustering with different window length selections. Windows were centered on 180 ms, the center of the 360 ms stimulation period. Clustering performance, measured both with a ground-truth performance measure (ARI) and an unsupervised cluster quality score (Silh...

Illustration of the EMD computation. Showing the first 5 iterations of the EMD algorithm on simple example cross correlation histograms. Each normalized cross-correlation (top and bottom) belongs to one epoch. In each step the mass is transported from the top epoch to the highlighted parts of the histogram and the histogram entries between which ma...

Example figure to illustrate the difference between homogeneous noise and patterned noise. Simulation parameters were λin = 0.35 spks/sample, λout = 0.05 spks/sample, Tepoch = 300 samples, Tpulse = 30 samples. Homogeneous noise was generated according to a homogeneous Poisson process, while each patterned noise epoch was an instantiation of a uniqu...

SPOTDisClust performance for cases where there are many noise epochs and few cluster epochs. Same settings as in Fig 1, but now using 750 noise epochs and only 30 epochs per cluster. Even though there is a very large number of noise epochs, t-SNE embedding is still able to reveal the separate clusters. (PDF)

Dependence of clustering performance on spike sorting errors resulting from collisions. The simulations are based on the same firing statistics reported for Fig 1. Neurons were divided into 10 groups of subsequent 5 neurons, each constituting a “virtual electrode”. Whenever two neurons fired simultaneously (i.e. at the same sample) within the group...

Application to neuronal data, matching Fig 8. For each multi-unit, we computed the spike count in the same temporal window as used for the SPOTDisClust clustering, denoted rik (epoch k, unit i). In (A), we then constructed a normalized population vector as rik′=rik/∑irik for each multi-unit i. We then constructed all pairwise distances between epoc...

Illustration of the SPOTDis computation. For each epoch (1), the cross-correlation is computed for each pair of neurons (2). These cross-correlations are then normalized to unit mass (3). For each pair of epochs and pair of neurons (4) we then compute the EMD. The EMDs are then averaged over all eligible neuron pairs (i.e. pairs of neurons active i...

Dependence of clustering performance on spike sorting contamination. (A) Five patterns were generated for a total of 330 neurons, with λin = 0.15 spks/sample, λout = 0.01 spks/sample. Each group of 11 subsequent neurons was assigned to one “virtual electrode”. From this virtual electrode, we then only “recorded” one neuron. The activity of each rec...