Biology subjects

Singer, W.

Publications and source records attributed to Singer, W..

4 recordsLinked to original sources

bioRxiv2018

Perceptual phenotypes: Perceptual gains and losses in synesthesia and schizophrenia

Individual differences in perception are widespread. Considering inter-individual variability, synesthetes experience stable additional sensations; schizophrenia patients suffer perceptual deficits in e.g. perceptual organization (alongside hallucinations and delusions). Is there a unifying principle explaining inter-individual variability in perception? There is good reason to believe perceptual experience results from inferential processes whereby sensory evidence is weighted by prior knowledge about the world. Different perceptual phenotypes may result from different precision weighting of sensory evidence and prior knowledge. We tested this hypothesis by comparing visibility thresholds in a perceptual hysteresis task across medicated schizophrenia patients, synesthetes, and controls. Participants rated the subjective visibility of stimuli embedded in noise while we parametrically manipulated the availability of sensory evidence. Additionally, precise long-term priors in synesthetes were leveraged by presenting either synesthesia-inducing or neutral stimuli. Schizophrenia patients showed increased visibility thresholds, consistent with overreliance on sensory evidence. In contrast, synesthetes exhibited lowered thresholds exclusively for synesthesia-inducing stimuli suggesting high-precision long-term priors. Additionally, in both synesthetes and schizophrenia patients explicit, short-term priors - introduced during the hysteresis experiment - lowered thresholds but did not normalize perception. Our results imply that distinct perceptual phenotypes might result from differences in the precision afforded to prior beliefs and sensory evidence, respectively.

neuroscience↗

bioRxiv2018

Surface color and predictability determine contextual modulation of V1 firing and gamma oscillations

The integration of direct bottom-up inputs with contextual information is a canonical motif in neocortical circuits. In area V1, neurons may reduce their firing rates when the (classical) receptive field input can be predicted by the spatial context. We previously hypothesized that gamma-synchronization (30-80Hz) provides a complementary signal to rates, encoding whether stimuli are predicted from spatial context by preferentially synchronizing neuronal populations receiving predictable inputs. Here we investigated how rates and synchrony are modulated by predictive context. Large uniform surfaces, which have high spatial predictability, strongly suppressed firing yet induced prominent gamma-synchronization, but only when they were colored. Yet, chromatic mismatches between center and surround, breaking predictability, strongly reduced gamma-synchronization while increasing firing rates. Differences between colors, including strong gamma-responses to red, arose because of stimulus adaptation to a full-screen background, with a prominent difference in adaptation between M- and L-cone signaling pathways. Thus, synchrony signals whether RF inputs are predicted from spatial context and may encode relationships across space, while firing rates increase when stimuli are unpredicted from the context.

neuroscience↗

bioRxiv2018

Why not record from every channel with a CMOS scanning probe?

It is an uninformative truism to state that the brain operates at multiple spatial and temporal scales, each with each own set of emergent phenomena. More worthy of attention is the point that our current understanding of it cannot clearly indicate which of these phenomenological scales are the significant contributors to the brains function and primary output (i.e. behaviour). Apart from the sheer complexity of the problem, a major contributing factor to this state of affairs is the lack of instrumentation that can simultaneously address these multiple scales without causing function altering damages to the underlying tissue. One important facet of this problem is that standard neural recording devices normally require one output connection per electrode. This limits the number of electrodes that can fit along the thin shafts of implantable probes generating a limiting balance between density and spread. Sharing a single output connection between multiple electrodes relaxes this constraint and permits designs of ultra-high density probes. Here we report the design and in-vivo validation of such a device, a complementary metal-oxide-semiconductor (CMOS) scanning probe with 1344 electrodes; the outcome of the European research project NeuroSeeker. We show that this design targets both local and global spatial scales by allowing the simultaneous recording of more than 1000 neurons spanning 7 functional regions with a single shaft. The neurons show similar recording longevity and signal to noise ratio to passive probes of comparable size and no adverse effects in awake or anesthetized animals. Addressing the data management of this device we also present novel visualization and monitoring methods. Using the probe with freely moving animals we show how accessing a number of cortical and subcortical brain regions offers a novel perspective on how the brain operates around salient behavioural events. Finally, we compare this probe with lower density, non CMOS designs (which have to adhere to the one electrode per output line rule). We show that an increase in density results in capturing neural firing patterns, undetectable by lower density devices, which correlate to self-similar structures inherent in complex naturalistic behaviour. To help design electrode configurations for future, even higher density, CMOS probes, recordings from many different brain regions were obtained with an ultra-dense passive probe.

neuroscience↗

bioRxiv2017

Stimulus content shapes cortical response statistics

Spike count correlations (SCCs) are ubiquitous in sensory cortices, are characterized by rich structure and arise from structured internal interactions. Yet, most theories of visual perception focus exclusively on the mean responses of individual neurons. Here, we argue that feedback interactions in primary visual cortex (V1) establish the context in which individual neurons process complex stimuli and that changes in visual context give rise to stimulus-dependent SCCs. Measuring V1 population responses to natural scenes in behaving macaques, we show that the fine structure of SCCs is stimulus-specific and variations in response correlations across-stimuli are independent of variations in response means. Moreover, we demonstrate that stimulus-specificity of SCCs in V1 can be directly manipulated by controlling the high-order structure of synthetic stimuli. We propose that stimulus-specificity of SCCs is a natural consequence of hierarchical inference where inferences on the presence of high-level image features modulate inferences on the presence of low-level features.

neuroscience↗