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Cowan, N.

Publications and source records attributed to Cowan, N..

14 recordsLinked to original sources

Manifolds for the neural representation of 3D spatial experience

The precision with which animals navigate and interact with objects depends in part on how their brains represent position and orientation in three dimensions. A central challenge is to explain within a common framework how neural systems ranging from insects to primates represent three-dimensional (3D) pose. Here we develop a framework based on the hypothesis that neural representations of pose lie on manifolds derived from the Special Euclidean Group, SE(3), which describes the full space of rigid-body positions and orientations in three dimensions. The framework shows how movement constraints, object geometry, and visual features jointly determine the topology of the resulting pose manifold, yielding a taxonomy that guides experimental tests. We apply the framework to derive low-dimensional manifolds for neural representations of 3D object orientation in macaque parietal cortex and head direction in the limbic systems of fruit bats, mice, and monkeys. This analysis also guides the construction of neuronal tuning functions that respect the topology determined by experimental conditions. Together, these results provide a common approach for linking the geometry of 3D pose to neural coding across species and brain systems.

neuroscience↗

Active Neural Representation of Stimulus Categories Outside of the Focus of Attention

Previous research on the brain correlates of working memory using functional magnetic resonance imaging (fMRI) and multivariate pattern analysis (MVPA) have shown that neural activity related to information currently needed to respond on a test is considered to be in the focus of attention (FoA). An ongoing controversy pertains to the neural representation of information in working memory that is not needed for the upcoming test but possibly for a subsequent one, which is considered to reside in an activated portion of long-term memory (aLTM). The key theoretical issue regarding aLTM is whether it corresponds solely to an activity-silent neural state. Here, by using a retrospective cuing task in which two arrays of stimuli from different categories were presented in succession on the same trial, and a pattern classifier trained on the first-presented category during the presentation of the second, we provide evidence that aLTM is associated with an active neural state. Specifically, the aLTM effect was demonstrated to be dissociable in direction from that related to the FoA, there was considerable overlap between brain regions representing information in a stronger form in the FoA and a weaker form in aLTM, and the two states appeared to be differentially subject to flexible cognitive control versus natural decay.

neuroscience↗

Hippocampal theta frequency as a readout of path-integration recalibration

Understanding how the brain represents hidden variables is a fundamental challenge. In navigation, the internal path-integration gain is often masked by external landmarks that override the path integrator. Path integration can recalibrate its gain when allothetic and idiothetic cues conflict, but the real-time dynamics of this process are hidden to direct observation. Here, we demonstrate that theta frequency provides an error signal between the observable hippocampal gain and the internal path-integration gain. Theta frequency decreased as conflict between landmark-driven hippocampal gain and path-integration gain increased and recovered as the path-integration gain recalibrated to the new gain. A continuous attractor model replicated these dynamics, suggesting that the theta-frequency drop is driven by the misalignment of allothetic and idiothetic inputs, reducing the excitatory drive to the network. Thus, theta frequency provides a real-time readout of internal gain-error signals, offering a novel methodology to estimate hidden cognitive variables through observable physiological oscillations.

neuroscience↗

Visual landmark coding and dynamic coupling with path integration circuits in area 29e of the rodent parahippocampal cortex

External landmarks anchor internal spatial representations. The neural mechanisms underlying this process and the sources of landmark signals remain unknown. We recorded neurons across five parahippocampal regions while rats navigated in a virtual reality apparatus, inducing conflict between self-motion and landmark cues. Area 29e, a parahippocampal field putatively homologous to primate area prostriata, maintained firing coupled to landmarks even when other regions decoupled from the landmarks. This decoupling was preceded by a decline of gamma-band influence from 29e to MEC and a concomitant decline of theta-modulated feedback from MEC to 29e. Area 29e also displayed weak theta modulation, strong gamma rhythmicity, strong egocentric head-direction tuning, and enhanced landmark contrast sensitivity. These findings provide strong evidence that 29e serves as a specialized visuospatial hub that provides landmark signals for anchoring parahippocampal spatial representations to the external world.

neuroscience↗

How tp1, an indirect wing steering muscle, stabilizes Drosophila's flight

Flapping flight is inherently unstable, requiring Drosophila to fine-tune their wing motions on a milliseconds timescale. Pioneering studies have shown that the direct steering muscles, which attach to the wing hinge, are important for generating these rapid flight reflexes. Recent connectome data, however, reveal that indirect steering muscles or tension muscles, which alter the mechanics of the thorax, receive some of the same synaptic inputs from the sensory apparatus as the direct steering muscles. This discovery suggests that the indirect steering muscles may also be important for flight control. Here, we show that the indirect tergopleural muscles indeed contribute substantially to stabilization, particularly for large pitch perturbations. We find that for small perturbations (less than 1000 deg/s), flies modulate their wing stroke amplitude to generate lift-based corrective torques, a strategy that has been previously documented. For larger perturbations, however, we observe that Drosophila engage an additional wing degree of freedom--the wing pitch angle--to leverage additional lift and drag forces during the corrective maneuver. Quasi-steady aerodynamic simulations reveal that this strategy minimizes power consumption, anaolgous to how some mammals (including humans) adjust their steady-state gaits in a near energy-optimal manner. Using optogenetics and a control theory framework we demonstrate that the tergopleural muscle is activated by a proportional gain component of a nonlinear PI controller responsible for determining the wing pitch angle during large perturbations. A simplified torsional-spring model for the wing hinge captures the changes in the wing pitch dynamics observed during correction maneuvers by using the tergopleural muscle to adjust the rest angle of the wing. These findings provide a striking example of reflex strategy selection in time-critical behaviors and underscores the vital role of indirect steering muscles in flight stabilization.

neuroscience↗

A multi-muscular, redundant strategy for free-flight roll stability

Whether recovering after a gust of wind, or rapidly saccading away from an oncoming predator, fruit flies show remarkable aerial dexterity about their body roll axis. Here, we investigated the detailed wing kinematic changes during free-flight roll motion and probed the neuromuscular basis for such changes. Consistent with previous work, we observed that flies manipulated the stroke amplitude difference between their wings to control their roll angle. Here, we show that flies are capable of achieving such changes by altering the stroke amplitude of either or both of their wings. Further we found that during corrections flies can also take advantage of an aerodynamically significant change in the angle of attack of their uppermost wing. Curiously, these corrective wing changes cannot be eliminated when motor neurons hypothesized to be used during roll maneuvers (i1, i2, b1, b2, and b3) are individually inhibited. However, free-flight optogenetic manipulations and quasi-steady aerodynamic calculations show that each of these motor neurons individually can effect kinematic changes consistent with a roll correction. Combining this evidence with an analysis of haltere inputs found in the BANC connectome, we propose that the observed robustness could be the result of two sets of muscular redundancies that receive shared inputs from haltere sensory afferents: one set, containing b1 and b2, is able to increase the stroke amplitude of the lower wing; while the other set, containing i1, i2, and b3, is able to decrease the stroke amplitude and wing pitch angle of the upper wing. Because of the redundancy in the input sensory information and output wing motion in the muscles in each cluster, the fly is able to perform roll stability maneuvers even when one of the constituent motor neurons is inhibited. This framework proposes new ways fast aerial maneuverability can be implemented when dealing with the flys most unstable rotational degree of freedom.

animal behavior and cognition↗

Sensitivity of Cerebellar Reaching Ataxia to Kinematic and Dynamic Demands

Individuals with cerebellar ataxia face significant challenges in controlling reaching, especially when multi-joint movements are involved. This study investigated the effects of kinematic and dynamic demands on reaching using a home-based virtual reality task. Participants with and without cerebellar ataxia reached to target locations designed to elicit a range of coordination strategies between shoulder and elbow joint movements. Compared with control subjects, cerebellar subjects presented greater initial reaching direction errors, larger hand trajectory curvatures, and more variability. Kinematic simulations indicated that early hand movement errors were sensitive to the required onset times and rates of joint movements and were most impaired when opposite direction joint movements were required (e.g., elbow extension with shoulder flexion). Dynamic analysis revealed that cerebellar participants movements were more impaired in reaching directions where interaction torques would normally assist the desired elbow and shoulder movements. These reach directions were also those that required joint movements in opposite directions. Overall, our data suggest that reaching deficits in cerebellar ataxia result from 1) the early-phase motion planning deficits that are exacerbated by stringent timing coordination requirements and 2) the inability to compensate for interaction torques, particularly when they assist the intended movement.

neuroscience↗

Muscle spindles provide flexible sensory feedback for movement sequences

Sensory feedback is essential for motor performance and must adapt to task demands. Muscle spindle afferents (MSAs) are a major primary source of feedback about movement, and their responses are readily modulated online by gain-controller fusimotor neurons and other mechanisms. They are therefore a powerful site for implementing flexible sensorimotor control. We recorded from MSAs innervating the jaw musculature during performance of a directed lick sequence task. Jaw MSAs encoded complex jaw-tongue kinematics. However, kinematic encoding alone accounted for less than half of MSA spiking variability. MSA coding of kinematics changed based on sequence progression (beginning, middle, or end of the sequence, or reward consumption), suggesting that MSAs are flexibly tuned across the task. Dynamic control of incoming feedback signals from MSAs may be a strategy for adaptable sensorimotor control during performance of complex behaviors.

neuroscience↗

Shape-shifting microgel automata controlled by DNA sequence instructions

Controlling material shapes using information-bearing molecular signals is central to the creation of autonomous, reconfigurable soft devices. While physical and chemical stimuli can direct simple material swelling, bending, or folding, it has been challenging to direct multi-step shape-change programs crucial for complex, robotic tasks. Here, we demonstrate gel automata-- sub-millimeter, photopatterned, highly swellable DNA gels--whose parts grow or shrink in response to easily designed DNA activator sequences, allowing for precisely controlled device articulation. We design and fabricate gel automata that reversibly transform between different letter shapes, and use neural networks to design automata that transform into every even or every odd numeral via designed reconfiguration programs. This sequential and repetitive metamorphosis of materials via chemical reorganization could dramatically advance our ability to manipulate micro-particles, cells, and tissues. One-Sentence SummaryPhotopatterned microgels follow sequences of DNA instructions to transform between complex, meaningful shapes such as letters and numerals.

bioengineering↗

Advances in non-invasive tracking of wave-type electric fish in natural and laboratory settings

Recent technological advances greatly improved the possibility to study freely behaving animals in natural conditions. However, many systems still rely on animal-mounted devices, which can already bias behavioral observations. Alternatively, animal behaviors can be detected and tracked in recordings of stationary sensors, e.g. video cameras. While these approaches circumvent the influence of animal-mounted devices, identification of individuals is much more challenging. We take advantage of the individual-specific electric fields electric fish generate by discharging their electric organ (EOD) to record and track their movement and communication behaviors without interfering with the animals themselves. EODs of complete groups of fish can be recorded with electrode arrays submerged in the water and then be tracked for individual fish. Here, we present an improved algorithm for tracking electric signals of wave-type electric fish with unprecedented accuracy. Our algorithm benefits from combining and refining previous approaches of tracking individual specific EOD frequencies (EODf) and spatial electric field properties. In this process, the similarity of signal pairs in extended data windows determines their tracking order, making the algorithm more robust against detection losses and intersections. We quantify the performance of the algorithm and show its application for a data set recorded with a 64-electrode array in a stream in the Llanos, Colombia, where we managed, for the first time, to track Apteronotus leptorhynchus over many days. These technological advances make electric fish a unique model system for a detailed analysis of social and communication behaviors, with strong implications for our research on sensory coding.

animal behavior and cognition↗

Neuromuscular embodiment of feedback control elements in Drosophila flight

While insects like Drosophila are flying, aerodynamic instabilities require that they make millisecond-timescale adjustments to their wing motion to stay aloft and on course. These stabilization reflexes can be modeled as a proportional-integral (PI) controller; however, it is unclear how such control might be instantiated in insects at the level of muscles and neurons. Here, we show that the b1 and b2 motor units--prominent components of the flys steering muscles system--modulate specific elements of the PI controller: the angular displacement (integral, I) and angular velocity (proportional, P), respectively. Moreover, these effects are observed only during the stabilization of pitch. Our results provide evidence for an organizational principle in which each muscle contributes to a specific functional role in flight control, a finding that highlights the power of using top-down behavioral modeling to guide bottom-up cellular manipulation studies.

animal behavior and cognition↗

Wide-Angle, Monocular Head Tracking using Passive Markers

Camera images can encode large amounts of visual information of an animal and its environment, enabling high fidelity 3D reconstruction of the animal and its environment using computer vision methods. Most systems, both markerless (e.g. deep learning based) and marker-based, require multiple cameras to track features across multiple points of view to enable such 3D reconstruction. However, such systems can be expensive and are challenging to set up in small animal research apparatuses. We present an open-source, marker-based system for tracking the head of a rodent for behavioral research that requires only a single camera with a potentially wide field of view. The system features a lightweight visual target and computer vision algorithms that together enable high-accuracy tracking of the six-degree-of-freedom position and orientation of the animals head. The system, which only requires a single camera positioned above the behavioral arena, robustly reconstructs the pose over a wide range of head angles (360{whitebullet} in yaw, and approximately {+/-}120{whitebullet} in roll and pitch). Experiments with live animals demonstrate that the system can reliably identify rat head position and orientation. Evaluations using a commercial optical tracker device show that the system achieves accuracy that rivals commercial multi-camera systems. Our solution significantly improves upon existing monocular marker-based tracking methods, both in accuracy and in allowable range of motion. The proposed system enables the study of complex behaviors by providing robust, fine-scale measurements of rodent head motions in a wide range of orientations.

neuroscience↗

Cerebellar patients have intact feedback control that can be leveraged to improve reaching

It is thought that the brain does not simply react to sensory feedback, but rather uses an internal model of the body to predict the consequences of motor commands before sensory feedback arrives. Time-delayed sensory feedback can then be used to correct for the unexpected--perturbations, motor noise, or a moving target. The cerebellum has been implicated in this predictive control process. Here we show that the feedback gain in patients with cerebellar ataxia matches that of healthy subjects, but that patients exhibit substantially more phase lag. This difference is captured by a computational model incorporating a Smith predictor in healthy subjects that is missing in patients, supporting the predictive role of the cerebellum in feedback control. Lastly, we improve cerebellar patients movement control by altering (phase advancing) the visual feedback they receive from their own self movement in a simplified virtual reality setup.

neuroscience↗

Variability in locomotor dynamics reveals the critical role of feedback in task control

Animals vary considerably in size, shape, and physiological features across individuals, but yet achieve behavioral performances that are virtually indistinguishable between conspecifics. We examined how animals compensate for morphophysiological variation by measuring the system dynamics of individual knifefish (Eigenmannia virescens) in a refuge tracking task. Kinematic measurements of Eigenmannia were used to generate individualized estimates of each fishs locomotor plant and controller revealing substantial variability between fish. To test the impact of this variability on behavioral performance, these models were used to perform simulated brain transplants--computationally swapping controllers and plants between individuals. We found that simulated closed-loop performance was robust to mismatch between plant and controller. This suggests that animals rely on feedback rather than precisely tuned neural controllers to compensate for morphophysiological variability.

neuroscience↗