High-fidelity estimates of spikes and subthreshold waveforms from 1-photon voltage imaging in vivo

April 6, 2021

The ability to probe the membrane potential of multiple genetically defined neurons simultaneously would have a profound impact on neuroscience research. Genetically encoded voltage indicators are a promising tool for this purpose, and recent developments have achieved a high signal-to-noise ratio in vivo with 1-photon fluorescence imaging. However, these recordings exhibit several sources of noise and signal extraction remains a challenge. We present an improved signal extraction pipeline, spike-guided penalized matrix decomposition-nonnegative matrix factorization (SGPMD-NMF), which resolves supra- and subthreshold voltages in vivo. The method incorporates biophysical and optical constraints. We validate the pipeline with simultaneous patch-clamp and optical recordings from mouse layer 1 in vivo and with simulated and composite datasets with realistic noise. We demonstrate applications to mouse hippocampus expressing paQuasAr3-s or SomArchon1, mouse cortex expressing SomArchon1 or Voltron, and zebrafish spines expressing zArchon1.

Michael E Xie, Yoav Adam, Linlin Z Fan, Urs L Böhm, Ian Kinsella, Ding Zhou, Marton Rozsa, Amrita Singh, Karel Svoboda, Liam Paninski, Adam E Cohen 


Connecting TDP-43 Pathology with Neuropathy

April 5, 2021

Transactive response DNA-binding protein 43 kDa (TDP-43), a multifunctional nucleic acid-binding protein, is a primary component of insoluble aggregates associated with several devastating nervous system disorders; mutations in TARDBP, its encoding gene, are a cause of familial amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here, we review established and emerging roles of TDP-43 and consider how its dysfunction impinges on RNA homeostasis in the nervous system, thereby contributing to neural degeneration. Notably, improper splicing of the axonal growth-associated factor STMN2 has recently been connected to TDP-43 dysfunction, providing a mechanistic link between TDP-43 proteinopathies and neuropathy. This review highlights how a deep understanding of the function of TDP-43 in the brain might be leveraged to develop new targeted therapies for several neurological disorders.


Joseph R Klim, Greta Pintacuda, Leslie A Nash, Irune Guerra San Juan, Kevin Eggan

Flexible scaling and persistence of social vocal communication

March 31, 2021


Innate vocal sounds such as laughing, screaming or crying convey one's feelings to others. In many species, including humans, scaling the amplitude and duration of vocalizations is essential for effective social communication1-3. In mice, female scent triggers male mice to emit innate courtship ultrasonic vocalizations (USVs)4,5. However, whether mice flexibly scale their vocalizations and how neural circuits are structured to generate flexibility remain largely unknown. Here we identify mouse neurons from the lateral preoptic area (LPOA) that express oestrogen receptor 1 (LPOAESR1 neurons) and, when activated, elicit the complete repertoire of USV syllables emitted during natural courtship. Neural anatomy and functional data reveal a two-step, di-synaptic circuit motif in which primary long-range inhibitory LPOAESR1 neurons relieve a clamp of local periaqueductal grey (PAG) inhibition, enabling excitatory PAG USV-gating neurons to trigger vocalizations. We find that social context shapes a wide range of USV amplitudes and bout durations. This variability is absent when PAG neurons are stimulated directly; PAG-evoked vocalizations are time-locked to neural activity and stereotypically loud. By contrast, increasing the activity of LPOAESR1 neurons scales the amplitude of vocalizations, and delaying the recovery of the inhibition clamp prolongs USV bouts. Thus, the LPOA disinhibition motif contributes to flexible loudness and the duration and persistence of bouts, which are key aspects of effective vocal social communication.


Jingyi Chen, Jeffrey E Markowitz, Varoth Lilascharoen, Sandra Taylor, Pete Sheurpukdi, Jason A Keller, Jennifer R Jensen, Byung Kook Lim, Sandeep Robert Datta, Lisa Stowers 

Illusions, Delusions, and Your Backwards Bayesian Brain: A Biased Visual Perspective

March 30, 2021

The retinal image is insufficient for determining what is "out there," because many different real-world geometries could produce any given retinal image. Thus, the visual system must infer which external cause is most likely, given both the sensory data and prior knowledge that is either innate or learned via interactions with the environment. We will describe a general framework of "hierarchical Bayesian inference" that we and others have used to explore the role of cortico-cortical feedback in the visual system, and we will further argue that this approach to "seeing" makes our visual systems prone to perceptual errors in a variety of different ways. In this deliberately provocative and biased perspective, we argue that the neuromodulator, dopamine, may be a crucial link between neural circuits performing Bayesian inference and the perceptual idiosyncrasies of people with schizophrenia.

Richard T Born, Gianluca M Bencomo 

Optimal policy for attention-modulated decisions explains human fixation behavior

March 26, 2021

Traditional accumulation-to-bound decision-making models assume that all choice options are processed with equal attention. In real life decisions, however, humans alternate their visual fixation between individual items to efficiently gather relevant information (Yang et al., 2016). These fixations also causally affect one's choices, biasing them toward the longer-fixated item (Krajbich et al., 2010). We derive a normative decision-making model in which attention enhances the reliability of information, consistent with neurophysiological findings (Cohen and Maunsell, 2009). Furthermore, our model actively controls fixation changes to optimize information gathering. We show that the optimal model reproduces fixation-related choice biases seen in humans and provides a Bayesian computational rationale for this phenomenon. This insight led to additional predictions that we could confirm in human data. Finally, by varying the relative cognitive advantage conferred by attention, we show that decision performance is benefited by a balanced spread of resources between the attended and unattended items.

Anthony Injoon Jang, Ravi Sharma, Jan Drugowitsch