Adrienne Fairhall

University of Washington Seattle | UW · Department of Physiology and Biophysics

Maintaining motor skills is crucial for an animal’s survival, enabling it to endure diverse perturbations throughout its lifespan, such as trauma, disease, and aging. What mechanisms orchestrate brain circuit reorganization and recovery to preserve the stability of behavior despite the continued presence of a disturbance? To investigate this questi...

How does neural activity drive muscles to produce behavior? The recent development of genetic lines in Hydra that allow complete calcium imaging of both neuronal and muscle activity, as well as systematic machine learning quantification of behaviors, makes this small cnidarian an ideal model system to understand and model the complete transformatio...

Inter-species comparisons are key to deriving an understanding of the behavioral and neural correlates of human cognition from animal models. We perform a detailed comparison of macaque monkey and human strategies on an analogue of the Wisconsin Card Sort Test, a widely studied and applied multi-attribute measure of cognitive function, wherein perf...

We propose centralized brain observatories for large-scale recordings of neural activity in mice and non-human primates coupled with cloud-based data analysis and sharing. Such observatories will advance reproducible systems neuroscience and democratize access to the most advanced tools and data.

Reliable execution of behaviors requires that brain circuits correct for variations in neuronal dynamics. Genetic perturbation of the majority of excitatory neurons in a brain region involved in song production in adult songbirds with stereotypical songs triggered severe degradation of their songs. The song fully recovered within two weeks, and sub...

Reliable execution of behaviors requires that brain circuits correct for variations in neuronal dynamics. Genetic perturbation of the majority of excitatory neurons in a brain region involved in song production in adult songbirds with stereotypical songs triggered severe degradation of their songs. The song fully recovered within two weeks, and sub...

Complex motor skills like playing piano require precise timing over long periods, without errors accumulating between subprocesses like the left and right hand movements. While biological models can produce motor-like sequences, how the brain quenches timing errors is not well understood. Motivated by songbirds, where the left and right brain nucle...

Excitatory cortical neurons show clear tuning to stimulus features, but the tuning properties of inhibitory neurons are ambiguous and have been the subject of a long debate. While inhibitory neurons have been considered to be largely untuned [1–4], recent studies show that some parvalbumin expressing (PV) neurons do show feature selectivity and par...

Interview with Adrienne Fairhall, who studies the relationship between neuronal circuitry and the functional algorithms of computation at the University of Washington.

Many motor skills are learned by comparing ongoing behavior to internal performance benchmarks. Dopamine neurons encode performance error in behavioral paradigms where error is externally induced, but it remains unknown whether dopamine also signals the quality of natural performance fluctuations. Here, we record dopamine neurons in singing birds a...

Dopamine plays a central role in motivating and modifying behavior, serving to invigorate current behavioral performance and guide future actions through learning. Here we examine how this single neuromodulator can contribute to such diverse forms of behavioral modulation. By recording from the dopaminergic reinforcement pathways of the Drosophila...

Measuring the activity of neuronal populations with calcium imaging can capture emergent functional properties of neuronal circuits with single cell resolution. However, the motion of freely behaving animals, together with the intermittent detectability of calcium sensors, can hinder automatic monitoring of neuronal activity and their subsequent fu...

Despite increased awareness of the lack of gender equity in academia and a growing number of initiatives to address issues of diversity, change is slow, and inequalities remain. A major source of inequity is gender bias, which has a substantial negative impact on the careers, work-life balance, and mental health of underrepresented groups in scienc...

Many motor skills are learned by comparing ongoing behavior to internal performance benchmarks. Dopamine neurons encode performance error in behavioral paradigms where error is externally induced, but it remains unknown if dopamine also signals the quality of natural performance fluctuations. Here we recorded dopamine neurons in singing birds and e...

The 2019 Society for Neuroscience Professional Development Workshop on Teaching reviewed current tools, approaches, and examples for teaching computation in neuroscience. Robert Kass described the statistical foundations that students need to properly analyze data. Pascal Wallisch compared MATLAB and Python as programming languages for teaching stu...

How does neural activity drive muscles to produce behavior? The recent development of genetic lines in Hydra that allow complete calcium imaging of both neuronal and muscle activity, as well as systematic machine learning quantification of behaviors, makes this small Cnidarian an ideal model system to understand and model the complete transformatio...

Large scientific projects in genomics and astronomy are influential not because they answer any single question but because they enable investigation of continuously arising new questions from the same data-rich sources. Advances in automated mapping of the brain's synaptic connections (connectomics) suggest that the complicated circuits underlying...

Single neurons can dynamically change the gain of their spiking responses to take into account shifts in stimulus variance. Moreover, gain adaptation can occur across multiple timescales. Here, we examine the ability of a simple statistical model of spike trains, the generalized linear model (GLM), to account for these adaptive effects. The GLM des...

Measuring the activity of neuronal populations with calcium imaging can capture emergent functional properties of neuronal circuits with single cell resolution. However, the motion of freely behaving animals, together with the intermittent detectability of calcium sensors, can hinder automatic long-term monitoring of the activity of individual neur...

Citation count has become one of the most important methods to evaluate a scientist’s contributions. In an extensive analysis of citations from a number of leading neuroscience journals, Dworkin and colleagues find evidence of gender bias in citation practices that can have an adverse impact on women’s careers.

Single neurons can dynamically change the gain of their spiking responses to account for shifts in stimulus variance. Moreover, gain adaptation can occur across multiple timescales. Here, we examine the ability of a simple statistical model of spike trains, the generalized linear model (GLM), to account for these adaptive effects. The GLM describes...

Sensory systems encounter remarkably diverse stimuli in the external environment. Natural stimuli exhibit timescales and amplitudes of variation that span a wide range. Mechanisms of adaptation, a ubiquitous feature of sensory systems, allow for the accommodation of this range of scales. Are there common rules of adaptation across different sensory...

The concept of 'neural coding' supposes that neural firing patterns in some sense represent some external correlate, whether sensory, motor, or structural knowledge about the world. While the implied existence of a one-to-one mapping between external referents and neural firing has been useful, the prevalence of adaptation challenges this. Adaptati...

Adaptation is a common principle that recurs throughout the nervous system at all stages of processing. This principle manifests in a variety of phenomena, from spike frequency adaptation, to apparent changes in receptive fields with changes in stimulus statistics, to enhanced responses to unexpected stimuli. The ubiquity of adaptation leads natura...

Sensory systems encounter remarkably diverse stimuli in the external environment. Natural stimuli exhibit timescales and amplitudes of variation that span a wide range. Mechanisms of adaptation, ubiquitous feature of sensory systems, allow for the accommodation of this range of scales. Are there common rules of adaptation across different sensory m...

Cognitive flexibility likely depends on modulation of the dynamics underlying how biological neural networks process information. While dynamics can be reshaped by gradually modifying connectivity, less is known about mechanisms operating on faster timescales. A compelling entrypoint to this problem is the observation that exploratory behaviors can...

Significance In this work, we show a way by which the nervous system maintains precise, stereotyped behavior in the face of environmental and neural changes. Through a model of bird song learning, we show how instability in neural representation of stable behavior can allow a system to more readily adapt and maintain performance with minimal cost....

Variability is a ubiquitous aspect of neural recordings. In an influential paper, Churchland et al. (2010) compiled data from many cortical areas to demonstrate that variability generally decreases upon presentation of a stimulus. What are the implications of this finding?

Mosquitoes rely on the integration of multiple sensory cues, including olfactory, visual, and thermal stimuli, to detect, identify and locate their hosts [1-4]. Although we increasingly know more about the role of chemosensory behaviours in mediating mosquito-host interactions [1], the role of visual cues remains comparatively less studied [3], and...

Mosquitoes rely on the integration of multiple sensory cues, including olfactory, visual, and thermal stimuli, to detect, identify and locate their hosts [1-4]. Although we increasingly know more about the role of chemosensory behaviours in mediating mosquito-host interactions [1], the role of visual cues remains comparatively less studied [3], and...

Cognitive flexibility, the adaptation of mental processing to changes in task demands, is thought to depend on biological neural networks' ability to rapidly modulate the dynamics governing how they process information. While extensive work has elucidated how network dynamics can be reshaped by slowly occurring structural changes, e.g. the gradual...

The combination of fluorescent probes with time-lapse microscopy allows for the visualization of the entire neuronal activity of small animals, such as worms or cnidarians, over a long period of time. However, large deformations of the animal combined with the natural intermittency of neuronal activity make robust automated tracking of firing fluor...

Mathematical and statistical models have played important roles in neuroscience, especially by describing the electrical activity of neurons recorded individually, or collectively across large networks. As the field moves forward rapidly, new challenges are emerging. For maximal effectiveness, those working to advance computational neuroscience wil...

Natural decision-making often involves extended decision sequences in response to variable stimuli with complex structure. As an example, many animals follow odor plumes to locate food sources or mates, but turbulence breaks up the advected odor signal into intermittent filaments and puffs. This scenario provides an opportunity to ask how animals u...

Partial correlation between heading change and crossing number, conditioned on x0 and tflight. Each panel corresponds to a different experiment. The x-axis shows x0 the x-position at the time of the crossing, and the y-axis shows the change in heading, time-averaged from 350 to 450 ms post-crossing. Each point corresponds to one crossing, with the...

Infotaxis history dependence for varied plume estimate parameters. Same layout as in Fig 3E–3H, but with different infotaxis parameters. In A-B, the source emission rate R is 1000Hz, and the turbulent diffusivity coefficient D is varied, as indicated in the panel titles. In C-E, the turbulent diffusivity coefficient D is 0.09 m2/s, with R varied, a...

Distributions of kinematic quantities in base model (before surge-cast or centerline-inferring features were added) vs. empirical data. Each panel shows the distribution of speeds (A), angular velocities (B), or crosswind positions (C) (calculated across all time point) of the empirical trajectories (black) vs. the trajectories generated by best-fi...

Effects of varying odor detection threshold on hybrid model analysis. Here we show the optimal surge-cast percentage in the surge-cast-infotaxis hybrid crossing model analysis introduced in Fig 6 as a function of the odor detection threshold used to generate and extract crossings from the trajectories. The points and error bars show the mean and st...

Positional differences between early and late plume crossings. Each panel shows the distribution of the upwind/downwind components of plume-crossing positions for either the early or late groups shown in Fig 3, measured at the time of the plume crossing. As in Fig 3, we have excluded all crossings occurring in the most upwind or most downwind 30 cm...

Position distributions for data and infotaxis results for different wind speeds. Equivalent to Fig 6A and 6D. A, B show position distributions for empirical data and infotaxis simulations in a wind tunnel with 0.4 m/s wind speeds, respectively. C, D show the same for a 0.6 m/s wind speed. (TIFF)

Determination of concentration thresholds for each experiment. The thick line shows the difference between the mean plume-crossing-triggered heading time-series for crossings above the threshold and the mean plume-crossing-triggered heading time-series for crossings below the threshold, time-averaged over the first one second following the plume cr...

Effects of varying odor detection threshold on history dependence analysis. In each panel the analysis from Fig 4 is performed on a set of plume crossings where crossings are defined as trajectory portions in which the odor concentration rises at least once above a minimum detection threshold (varying by panel and listed in panel titles). All panel...

Significance Trial-and-error learning requires variation in successive trials, but the source of such variability is unknown. We describe a unique striatal glutamatergic neuron in the zebra finch. This neuron exerts a potent, dopamine-regulated action on pallidal output neurons that modifies neuronal firing statistics in the circuit known to contri...

High-frequency “burst” clusters of spikes are a generic output pattern of many neurons. While bursting is a ubiquitous computational feature of different nervous systems across animal species, the encoding of synaptic inputs by bursts is not well understood. We find that bursting neurons in the rodent thalamus employ “multiplexing” to differentiall...

Designing brain-computer interfaces (BCIs) that can be used in conjunction with ongoing motor behavior requires an understanding of how neural activity co-opted for brain-control interacts with existing neural circuits. BCIs may be used to regain lost motor function after stroke or traumatic brain injury, for instance, provided that a neural contro...

Neuroscience research is becoming increasingly more collaborative and interdisciplinary with partnerships between industry and academia and insights from fields beyond neuroscience. In the age of institutional initiatives and multi-investigator collaborations, scientists from around the world shared their perspectives on the effectiveness of large-...

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). What are the neuronal mechanisms responsible for these changes and how does targeted stimulation by a BBCI shape population-level synaptic connect...

As information flows through the brain, neuronal firing progresses from encoding the world as sensed by the animal to driving the motor output of subsequent behavior. One of the more tractable goals of quantitative neuroscience is to develop predictive models that relate the sensory or motor streams with neuronal firing. Here we review and contrast...

The nervous system extracts information from its environment and distributes and processes that information to inform and drive behaviour. In this task, the nervous system faces a type of data analysis problem, for, while a visual scene may be overflowing with information, reaching for the television remote before us requires extraction of only a r...

To attract females during courtship, Drosophila melanogaster males sing songs with motifs of varying temporal structure. In this issue of Neuron, Clemens et al. (2015) identify a song feature indicating male fitness and propose a neural mechanism for how it may be extracted from the auditory signal by female flies. To attract females during courtsh...

All moving animals, including flies [1-3], sharks [4], and humans [5], experience a dynamic sensory landscape that is a function of both their trajectory through space and the distribution of stimuli in the environment. This is particularly apparent for mosquitoes, which use a combination of olfactory, visual, and thermal cues to locate hosts [6-10...

In a significant new study, Mitra et al. (1) demonstrate the existence of reproducible temporal patterns of spontaneous activity from human functional magnetic resonance imaging (fMRI) recordings. This finding and the novel methods used to demonstrate it bring the question of the role of temporally patterned activity into the domain of human cognit...

What are the features of movement encoded by changing motor commands? Do motor commands encode movement independently or can they be represented in a reduced set of signals (i.e. synergies)? Motor encoding poses a computational and practical challenge because many muscles typically drive movement, and simultaneous electrophysiology recordings of al...

Diverse ion channels and their dynamics endow single neurons with complex biophysical properties. These properties determine the heterogeneity of cell types that make up the brain, as constituents of neural circuits tuned to perform highly specific computations. How do biophysical properties of single neurons impact network function? We study a set...

Unlabelled: While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates. In equivalent spiking implementations, firing is assumed to be random such that averaging across p...

In trying to understand the structure and dynamics of sensory neural representations, it has been productive to examine the complex structure of natural images to discover the nature of the task that the nervous system performs. Two different forms of adaptation help sensory systems to handle the large variations and multiple spatial and temporal s...

Spontaneous synchronous activity (SSA) that propagates as electrical waves is found in numerous CNS structures and is critical for normal development, but the mechanisms of generation of such activity are not clear. In previous work, we showed that the ventrolateral piriform cortex is uniquely able to initiate SSA in contrast to the dorsal neocorte...

The linear-nonlinear cascade model (LN model) has proven very useful in representing a neural system's encoding properties, but has proven less successful in reproducing the firing patterns of individual neurons whose behavior is strongly dependent on prior firing history. While the cell's behavior can still usefully be considered as feature detect...

Significance Visually driven behaviors of Drosophila have become a model system to study how neural circuits process sensory information. Here, we show that one of the computations performed by this system is temporal integration of visual motion. We provide evidence of how this computation might be performed by measuring the activity of identified...

Advances in experimental techniques, including behavioral paradigms using rich stimuli under closed loop conditions and the interfacing of neural systems with external inputs and outputs, reveal complex dynamics in the neural code and require a revisiting of standard concepts of representation. High-throughput recording and imaging methods along wi...

Adaptation is a fundamental computational motif in neural processing. To maintain stable perception in the face of rapidly shifting input, neural systems must extract relevant information from background fluctuations under many different contexts. Many neural systems are able to adjust their input-output properties such that an input's ability to t...

The analysis of stimulus/response patterns using information theoretic approaches requires the full probability distribution of stimuli and response. Recent progress in using information-based tools to understand circuit function has advanced understanding of neural coding at the single cell and population level. In advances over traditional revers...

A neuron transforms its input into output spikes, and this transformation is the basic unit of computation in the nervous system. The spiking response of the neuron to a complex, time-varying input can be predicted from the detailed biophysical properties of the neuron, modeled as a deterministic nonlinear dynamical system. In the tradition of neur...

Many neural systems are equipped with mechanisms to efficiently encode sensory information. To represent natural stimuli with time-varying statistical properties, neural systems should adjust their gain to the inputs' statistical distribution. Such matching of dynamic range to input statistics has been shown to maximize the information transmitted...

Adaptive processes over many timescales endow neurons with sensitivity to stimulus changes over a similarly wide range of scales. Although spike timing of single neurons can precisely signal rapid fluctuations in their inputs, the mean firing rate can convey information about slower-varying properties of the stimulus. Here, we investigate the firin...

In transforming sensory data into voltage signals, the strategies employed by neurons and neural systems have been shown to be adaptive: as the statistical properties of the environment change, the mapping from input to output also changes, often in such a way as to maximize information transmission. In large part, neuronal dynamics arise from volt...

Nucleus laminaris (NL) neurons encode interaural time difference (ITD), the cue used to localize low-frequency sounds. A physiologically based model of NL input suggests that ITD information is contained in narrow frequency bands around harmonics of the sound frequency. This suggested a theory, which predicts that, for each tone frequency, there is...

The halteres of dipteran insects are essential sensory organs for flight control. They are believed to detect Coriolis and other inertial forces associated with body rotation during flight. Flies use this information for rapid flight control. We show that the primary afferent neurons of the haltere's mechanoreceptors respond selectively with high t...

The relationship between a neuron's complex inputs and its spiking output defines the neuron's coding strategy. This is frequently and effectively modeled phenomenologically by one or more linear filters that extract the components of the stimulus that are relevant for triggering spikes and a nonlinear function that relates stimulus to firing proba...

Neuronal responses are often characterized by the firing rate as a function of the stimulus mean, or the f-I curve. We introduce a novel classification of neurons into Types A, B-, and B+ according to how f-I curves are modulated by input fluctuations. In Type A neurons, the f-I curves display little sensitivity to input fluctuations when the mean...

Adaptation is a hallmark of sensory function. Adapting optimally requires matching the dynamics of adaptation to those of changes in the stimulus distribution. Here we show that the dynamics of adaptation in the responses of mouse retinal ganglion cells depend on stimulus history. We hypothesized that the accumulation of evidence for a change in th...

The relationship between a neuron's complex inputs and its s piking output defines the neuron's coding strategy. This is frequently and effectively modeled phenomenologically by a linear filter that extracts the components of the stimulus that are relevant for triggering spikes, and a nonlinear function that relates stim- ulus to firing probability...

Neural systems adapt to changes in stimulus statistics. However, it is not known how stimuli with complex temporal dynamics drive the dynamics of adaptation and the resulting firing rate. For single neurons, it has often been assumed that adaptation has a single time scale. We found that single rat neocortical pyramidal neurons adapt with a time sc...

Firing Rate of the LIF Model with Noisy Stimuli. (0.09 MB DOC)