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Response variability and information transfer in directional neurons of the mammalian horizontal optokinetic system

VISUAL NEUROSCIENCE 2000年第2期17卷 207-215页

作者： Clifford, CWG Ibbotson, MR Macquarie Univ Dept Psychol Sydney NSW 2109 Australia Australian Natl Univ Ctr Visual Sci Res Sch Biol Sci Canberra ACT 2601 Australia

This study is concerned with how information about the direction of visual motion is encoded by motion-sensitive neurons. Motion-sensitive neurons are usually studied using stimuli unchanging in speed and direction over several seconds. Recently, it has been suggested that neuronal responses to more naturalistic stimuli cannot be understood on the basis of experiments with constant-motion stimuli (de Ruyter van Steveninck et al., 1997). We measured the variability and information content of spike trains recorded from directional neurons in the nucleus of the optic tract (NOT) of the wallaby, Macropus eugenii, in response to constant and time-varying motion. While the NOT forms part of the mammalian optokinetic system, we have shown previously that the responses of its directional neurons resemble those of insect H1 in many respects (Ibbotson ct al., 1994). We find that directional neurons in the wallaby NOT respond with lower variability and higher rates of information transmission to time-varying stimuli than to constant motion. The difference in response variability is predicted by an inhomogeneous Poisson model of neuronal spiking incorporating an absolute refractory period of 2 ms during which no subsequent spike can be fired. Refractoriness imposes structure on the spike train, reducing variability (de Ruyter van Steveninck & Bialek, 1988;Berry & Meister, 1998). A given refractory period has a greater impact when firing rates are high, as for the responses of NOT neurons to time-varying stimuli. It is in just these cases that variability in experimentally observed spike trains is lowest. Thus, differences in response variability do not necessarily imply that different models are required to predict neuronal responses to constant- and time-varying motion stimuli.

关键词： vision motion nucleus of the optic tract wallaby neural coding

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Descending neurons of the hoverfly respond to pursuits of artificial targets

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CURRENT BIOLOGY 2023年第20期33卷 4392-+页

作者： Ogawa, Yuri Nicholas, Sarah Thyselius, Malin Leibbrandt, Richard Nowotny, Thomas Knight, James C. Nordstrom, Karin Flinders Univ S Australia Flinders Hlth & Med Res Inst GPO Box 2100 Adelaide SA 5001 Australia Uppsala Univ Dept Med Cell Biol S-75123 Uppsala Sweden Orebro Univ Sch Med Sci Fac Med & Hlth S-70182 Orebro Sweden Flinders Univ S Australia Coll Sci & Engn GPO Box 2100 Adelaide SA 5001 Australia Univ Sussex Sch Engn & Informat Brighton BN1 9QJ E Sussex England

Many animals use motion vision information to control dynamic behaviors. Predatory animals, for example, show an exquisite ability to detect rapidly moving prey, followed by pursuit and capture. Such target detec-tion is not only used by predators but is also important in conspecific interactions, such as for male hoverflies defending their territories against conspecific intruders. Visual target detection is believed to be subserved by specialized target-tuned neurons found in a range of species, including vertebrates and arthropods. How-ever, how these target-tuned neurons respond to actual pursuit trajectories is currently not well understood. To redress this, we recorded extracellularly from target-selective descending neurons (TSDNs) in male Eri-stalis tenax hoverflies. We show that they have dorso-frontal receptive fields with a preferred direction up and away from the visual midline. We reconstructed visual flow fields as experienced during pursuits of arti-ficial targets (black beads). We recorded TSDN responses to six reconstructed pursuits and found that each neuron responded consistently at remarkably specific time points but that these time points differed between neurons. We found that the observed spike probability was correlated with the spike probability predicted from each neuron's receptive field and size tuning. Interestingly, however, the overall response rate was low, with individual neurons responding to only a small part of each reconstructed pursuit. In contrast, the TSDN population responded to substantially larger proportions of the pursuits but with lower probability. This large variation between neurons could be useful if different neurons control different parts of the behav-ioral output.

关键词： target motion insect vision motion vision hoverfly descending neuron target pursuit neural coding naturalistic stimuli modeling prediction

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Movement-specific signaling is differentially distributed across motor cortex layer 5 projection neuron classes

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CELL REPORTS 2022年第6期39卷 000-000页

作者： Currie, Stephen P. Ammer, Julian J. Premchand, Brian Dacre, Joshua Wu, Yufei Eleftheriou, Constantinos Colligan, Matt Clarke, Thomas Mitchell, Leah Faisal, A. Aldo Hennig, Matthias H. Duguid, Ian Univ Edinburgh Edinburgh Med Sch Biomed Sci Ctr Discovery Brain Sci Hugh Robson BldgGeorge Sq Edinburgh EH8 9XD Midlothian Scotland Univ Edinburgh Edinburgh Med Sch Biomed Sci Patrick Wild Ctr Hugh Robson BldgGeorge Sq Edinburgh EH8 9XD Midlothian Scotland Univ Edinburgh Edinburgh Med Sch Biomed Sci Simons Initiat Developing Brain Edinburgh EH8 9XD Midlothian Scotland Imperial Coll London Dept Bioengn London SW7 2AZ England Imperial Coll London Dept Comp London SW7 2AZ England MRC London Inst Med Sci London W12 0NN England Univ Edinburgh Sch Informat Inst Adapt & Neural Computat Edinburgh EH8 9AB Midlothian Scotland Univ Freiburg Fac Biol Optophysiol D-79100 Freiburg Germany ASTAR Infocomm Res 1 Fusionopolis Way21-01 Connexis South Tower Singapore 138632 Singapore

Motor cortex generates descending output necessary for executing a wide range of limb movements. Although movement-related activity has been described throughout motor cortex, the spatiotemporal organization of movement-specific signaling in deep layers remains largely unknown. Here we record layer 5B population dynamics in the caudal forelimb area of motor cortex while mice perform a forelimb push/ pull task and find that most neurons show movement-invariant responses, with a minority displaying movement specificity. Using cell-type-specific imaging, we identify that invariant responses dominate pyramidal tract (PT) neuron activity, with a small subpopulation representing movement type, whereas a larger proportion of intratelencephalic (IT) neurons display movement-type-specific signaling. The proportion of IT neurons decoding movement-type peaks prior to movement initiation, whereas for PT neurons, this occurs during movement execution. Our data suggest that layer 5B population dynamics largely reflect movement-invariant signaling, with information related to movement-type being routed through relatively small, distributed subpopulations of projection neurons.

关键词： motor cortex action-specific calcium imaging motor control layer 5B neural coding motor behavior decoding object manipulation cortical silencing

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Stimulus-invariant aspects of the retinal code drive discriminability of natural scenes

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2024年第52期121卷 e2313676121页

作者： Hoshal, Benjamin D. Holmes, Caroline M. Bojanek, Kyle Salisbury, Jared M. Berry II, Michael J. Marre, Olivier Palmer, Stephanie E. Harvard Univ Dept Organism & Evolutionary Biol Cambridge MA 02138 USA Univ Chicago Comm Computat Neurosci Dept Organismal Biol & Anat Chicago IL 60637 USA Princeton Univ Dept Phys Princeton NJ 08540 USA Univ Chicago Dept Organismal Biol & Anat Chicago IL 60637 USA Univ Chicago Dept Phys Chicago IL 60637 USA Princeton Univ Princeton Neurosci Inst Dept Mol Biol Princeton NJ 08540 USA Sorbonne Univ Inst Vis INSERM F-75012 Paris France Princeton Univ Ctr Phys Biol Funct Dept Phys Princeton NJ 08540 USA

Everything that the brain sees must first be encoded by the retina, which maintains a reliable representation of the visual world in many different, complex natural scenes while also adapting to stimulus changes. This study quantifies whether and how the brain selectively encodes stimulus features about scene identity in complex naturalistic environments. While a wealth of previous work has dug into the static and dynamic features of the population code in retinal ganglion cells (RGCs), less is known about how populations form both flexible and reliable encoding in natural moving scenes. We record from the larval salamander retina responding to five different natural movies, over many repeats, and use these data to characterize the population code in terms of single-cell fluctuations in rate and pairwise couplings between cells. Decomposing the population code into independent and cell-cell interactions reveals how broad scene structure is encoded in the retinal output. while the single-cell activity adapts to different stimuli, the population structure captured in the sparse, strong couplings is consistent across natural movies as well as synthetic stimuli. We show that these interactions contribute to encoding scene identity. We also demonstrate that this structure likely arises in part from shared bipolar cell input as well as from gap junctions between RGCs and amacrine cells.

关键词： neural coding natural scenes retina neural computation population code

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Single cortical neurons as deep artificial neural networks

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NEURON 2021年第17期109卷 2727-+页

作者： Beniaguev, David Segev, Idan London, Michael Hebrew Univ Jerusalem Edmond & Lily Safra Ctr Brain Sci ELSC IL-91904 Jerusalem Israel Hebrew Univ Jerusalem Dept Neurobiol IL-91904 Jerusalem Israel

Utilizing recent advances in machine learning, we introduce a systematic approach to characterize neurons' input/output (I/O) mapping complexity. Deep neural networks (DNNs) were trained to faithfully replicate the I/O function of various biophysical models of cortical neurons at millisecond (spiking) resolution. A temporally convolutional DNN with five to eight layers was required to capture the I/O mapping of a realistic model of a layer 5 cortical pyramidal cell (L5PC). This DNN generalized well when presented with inputs widely outside the training distribution. When NMDA receptors were removed, a much simpler network (fully connected neural network with one hidden layer) was sufficient to fit the model. Analysis of the DNNs' weight matrices revealed that synaptic integration in dendritic branches could be conceptualized as pattern matching from a set of spatiotemporal templates. This study provides a unified characterization of the computational complexity of single neurons and suggests that cortical networks therefore have a unique architecture, potentially supporting their computational power.

关键词： deep learning machine learning synaptic integration cortical pyramidal neuron compartmental model dendritic nonlinearities dendritic computation neural coding NMDA spike calcium spike

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Prelimbic neuron assemblies with delayed activation encode the economic decision-making process in a bandit game

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BEHAVIOURAL BRAIN RESEARCH 2023年第1期447卷 114419页

作者： Ma, Xiao Wang, Zhenni Lou, Shihao Guo, Hui Yang, Yupeng Univ Sci & Technol China Sch Life Sci Div Life Sci & Med CAS Key Lab Brain Funct & Dis Hefei 230027 Peoples R China

The medial prefrontal cortex (mPFC) is critical to an animal's value-based decision-making process. However, due to heterogeneity of local mPFC neurons, which neuron group and how it contributes to the alteration of the animal's decision is yet to be explored. And the effect of empty reward in this process is often neglected. Here, we adopted a two-port bandit game paradigm for mice and applied synchronized calcium imaging to the prelimbic area of the mPFC. The results showed that neurons recruited in the bandit game exhibit three distinct firing patterns. Specially, neurons with delayed activation (deA neurons1) carried exclusive information on reward type and changes of choice value. We demonstrated that these deA neurons were essential for the construction of choice-outcome correlation and the trial-to-trial modification of decision. Additionally, we found that in a long-term gambling game, members of the deA neuron assembly were dynamically shifting while maintaining the function, and the importance of empty reward feedbacks were gradually elevated to the same level as reward. Together, these results revealed a vital role for prelimbic deA neurons in the gambling tasks and a new perspective on the encoding of economic decision-making.

关键词： Medial prefrontal cortex Calcium imaging Decision-making neural coding Choice value Empty reward

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The effect of stimulus intensity on neural envelope tracking

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HEARING RESEARCH 2021年 403卷 108175-108175页

作者： Verschueren, Eline Vanthornhout, Jonas Francart, Tom KU Leuven Univ Leuven Res Grp Expt Otorhinolaryngol ExpORL Dept Neurosci Herestr 49Bus 721 B-3000 Leuven Belgium

Objectives In recent years, there has been significant interest in recovering the temporal envelope of a speech signal from the neural response to investigate neural speech processing. The research focus is now broadening from neural speech processing in normal-hearing listeners towards hearing-impaired listeners. When testing hearing-impaired listeners, speech has to be amplified to resemble the effect of a hearing aid and compensate for peripheral hearing loss. Today it is not known with certainty how or if neural speech tracking is influenced by sound amplification. As these higher intensities could influence the outcome, we investigated the influence of stimulus intensity on neural speech tracking. Design We recorded the electroencephalogram (EEG) of 20 normal-hearing participants while they listened to a narrated story. The story was presented at intensities from 10 to 80 dB A. To investigate the brain responses, we analyzed neural tracking of the speech envelope by reconstructing the envelope from the EEG using a linear decoder and by correlating the reconstructed with the actual envelope. We investigated the delta (0.5-4 Hz) and the theta (4-8 Hz) band for each intensity. We also investigated the latencies and amplitudes of the responses in more detail using temporal response functions, which are the estimated linear response functions between the stimulus envelope and the EEG. Results neural envelope tracking is dependent on stimulus intensity in both the TRF and envelope reconstruction analysis. However, provided that the decoder is applied to the same stimulus intensity as it was trained on, envelope reconstruction is robust to stimulus intensity. Besides, neural envelope tracking in the delta (but not theta) band seems to relate to speech intelligibility. Similar to the linear decoder analysis, TRF amplitudes and latencies are dependent on stimulus intensity: The amplitude of peak 1 (30-50 ms) increases, and the latency of peak 2 (140-160 ms) decreases wi

关键词： neural coding Natural speech Stimulus intensity EEG Speech understanding

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Speed-invariant encoding of looming object distance requires power law spike rate adaptation

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2013年第33期110卷 13624-13629页

作者： Clarke, Stephen E. Naud, Richard Longtin, Andre Maler, Leonard Univ Ottawa Dept Cellular & Mol Med Ottawa ON K1H 8M5 Canada Univ Ottawa Dept Phys Ottawa ON K1H 8M5 Canada

neural representations of a moving object's distance and approach speed are essential for determining appropriate orienting responses, such as those observed in the localization behaviors of the weakly electric fish, Apteronotus leptorhynchus. We demonstrate that a power law form of spike rate adaptation transforms an electroreceptor afferent's response to "looming" object motion, effectively parsing information about distance and approach speed into distinct measures of the firing rate. Neurons with dynamics characterized by fixed time scales are shown to confound estimates of object distance and speed. Conversely, power law adaptation modifies an electroreceptor afferent's response according to the time scales present in the stimulus, generating a rate code for looming object distance that is invariant to speed and acceleration. Consequently, estimates of both object distance and approach speed can be uniquely determined from an electroreceptor afferent's firing rate, a multiplexed neural code operating over the extended time scales associated with behaviorally relevant stimuli.

关键词： spike frequency adaptation perceptual invariance sensory transformations neural coding

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Interaction between neuronal encoding and population dynamics during categorization task switching in parietal cortex

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NEURON 2021年第4期109卷 700-712.e4页

作者： Mohan, Krithika Zhu, Ou Freedman, David J. Univ Chicago Dept Neurobiol Chicago IL 60637 USA Univ Chicago Grossman Inst Neurosci Quantitat Biol & Human Beh Chicago IL 60637 USA

Primates excel at categorization, a cognitive process for assigning stimuli into behaviorally relevant groups. Categories are encoded in multiple brain areas and tasks, yet it remains unclear how neural encoding and dynamics support cognitive tasks with different demands. We recorded from parietal cortex during flexible switching between categorization tasks with distinct cognitive and motor demands and also studied recurrent neural networks (RNNs) trained on the same tasks. In the one-interval categorization task (OIC), monkeys rapidly reported their decisions with a saccade. In the delayed match-to-category (DMC) task, monkeys decided whether sequentially presented stimuli were categorical matches. Neuronal category encoding generalized across tasks, but categorical encoding was more binary-like in the DMC task and more graded in the OIC task. Furthermore, analysis of trained RNNs supports the hypothesis that binary-like encoding in DMC arises through compression of graded feature encoding by attractor dynamics underlying stimulus maintenance and/or comparison in working memory.

关键词： Attractor dynamics Parietal cortex Categorization Task switching neural coding Working memory Recurrent neural network

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Statistical analysis and optimality of neural systems

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NEURON 2021年第7期109卷 1227-1241.e5页

作者： Mlynarski, Wiktor Hledik, Michal Sokolowski, Thomas R. Tkacik, GaSper IST Austria Campus 1 A-3400 Klosterneuburg Austria Frankfurt Inst Adv Studies Ruth Moufang Str 1 D-60438 Frankfurt Germany

Normative theories and statistical inference provide complementary approaches for the study of biological systems. A normative theory postulates that organisms have adapted to efficiently solve essential tasks and proceeds to mathematically work out testable consequences of such optimality;parameters that maximize the hypothesized organismal function can be derived ab initio, without reference to experimental data. In contrast, statistical inference focuses on the efficient utilization of data to learn model parameters, without reference to any a priori notion of biological function. Traditionally, these two approaches were developed independently and applied separately. Here, we unify them in a coherent Bayesian framework that embeds a normative theory into a family of maximum-entropy ?optimization priors.?This family defines a smooth interpolation between a data-rich inference regime and a data-limited prediction regime. Using three neuroscience datasets, we demonstrate that our framework allows one to address fundamental challenges relating to inference in high-dimensional, biological problems.

关键词： neural coding evolution optimization statistical inference

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