Alexander Gail

Neural Dynamics in Monkey Parietal Reach Region Reflect Context-Specific Sensorimotor Transformations

We investigated the neural dynamics of sensorimotor transformations in the parietal reach region (PRR) of monkeys. To dissociate sensory from motor goal representations, we used a memory-guided anti-reach task. The monkeys had to reach either to a visually instructed, memorized peripheral target position (pro-reach) or to a diametrically opposed position (anti) while keeping central ocular fixation. Pro- and anti-reaches were randomly interleaved and indicated by a color instruction from the beginning of each trial. We analyzed spatiotemporal single-cell tuning and performed time-resolved population decoding to quantify the dynamic representation of the spatial visual cue, the reach goal, and the currently valid task rule (pro/anti mapping). Sensory information regarding the visual cue position was represented weakly during a short period of cue visibility. PRR predominantly encoded the reach goal from the end of the cue period on. The representation of the reach goal in the memory task evolves later for the anti- compared with pro-reaches, consistent with a 40–50 ms difference in reaction time between the two task rules. The task rule could be decoded before the appearance of the spatial cue, which indicates that abstract rule information is present in PRR that is independent of spatial cue or motor goal representations. Our findings support the hypothesis that PRR immediately translates current sensory information into reach movement plans, rather than storing the memorized cue location in the instructed-delay task. This finding indicates that PRR represents integrated knowledge on spatial sensory information combined with abstract behavioral rules to encode the desired movement goal.

Implementation of spatial transformation rules for goal-directed reaching via gain modulation in monkey parietal and premotor cortex.

Planning goal-directed movements requires the combination of visuospatial with abstract contextual information. Our sensory environment constrains possible movements to a certain extent. However, contextual information guides proper choice of action in a given situation and allows flexible mapping of sensory instruction cues onto different motor actions. We used anti-reach tasks to test the hypothesis that spatial motor-goal representations in cortical sensorimotor areas are gain modulated by the behavioral context to achieve flexible remapping of spatial cue information onto arbitrary motor goals. We found that gain modulation of neuronal reach goal representations is commonly induced by the behavioral context in individual neurons of both, the parietal reach region (PRR) and the dorsal premotor cortex (PMd). In addition, PRR showed stronger directional selectivity during the planning of a reach toward a directly cued goal (pro-reach) compared with an inferred target (anti-reach). PMd, however, showed stronger overall activity during reaches toward inferred targets compared with directly cued targets. Based on our experimental evidence, we suggest that gain modulation is the computational mechanism underlying the integration of spatial and contextual information for flexible, rule-driven stimulus–response mapping, and thereby forms an important basis of goal-directed behavior. Complementary contextual effects in PRR versus PMd are consistent with the idea that posterior parietal cortex preferentially represents sensory-driven, “automatic” motor goals, whereas frontal sensorimotor areas are stronger engaged in the representation of rule-based, “inferred” motor goals.

Flexible cortical gamma-band correlations suggest neural principles of visual processing

We summarize recent studies of our group from the primary visual cortex V1 of behaving monkeys referring to the hypothesis of spatial feature binding by γ-synchronization (30-90 Hz). In agreement with this hypothesis the data demonstrates decoupling of γ-activities among neural groups representing figure and ground. As γ-synchronization in V1 is restricted to cortical ranges of few millimeters, feature binding may equivalently be restricted in visual space. Closer inspection shows that the restriction in synchrony is due to far-reaching travelling γ-waves with changing phase coupling. Based on this observation we extend the initial binding-by-synchronization hypothesis and suggest object continuity to be coded by phase continuity. It is further argued that the spatial phase changes of the V1 γ-waves in general will also limit lateral phase coupling to higher levels of processing. Instead of phase-locked γ-coupling, corticocortical cooperation among γ-processes may be mediated by mutual amplitude modulations that are more reliable than phase synchrony over larger distances. The relevance of this concept of corticocortical binding is demonstrated with subdural recordings from human subjects performing cognitive tasks. The experimental results are discussed on the basis of network models with spiking neurons.

Different types of signal coupling in the visual cortex related to neural mechanisms of associative Processing and perception

The hypothesis of object representation by synchronization in the visual cortex has been supported by our recent experiments in monkeys. They demonstrated local synchrony among /spl gamma/ activities (30-90 Hz) and their perceptual modulation, according to the rules of figure-ground segregation. However, /spl gamma/-synchrony in primary visual cortex is restricted to few mm, challenging the synchronization hypothesis for larger cortical object representations. The restriction is due to randomly changing phase relations among locally synchronized patches which, however, form continuous waves of /spl gamma/-activity, traveling across object representations. The phase continuity of these waves may support coding of object continuity. Interactions across still larger distances, measured among cortical areas in human data, involve amplitude envelopes of /spl gamma/ signals. Based on models with spiking neurons we discuss potentially underlying mechanisms. Most important for /spl gamma/ synchronization are local facilitatory connections with distance-dependent delays. They also explain the occurrence of /spl gamma/ waves and the restriction of /spl gamma/-synchrony. Fast local feedback inhibition generates /spl gamma/ oscillations and supports local synchrony, while slow shunting inhibitory feedback supports figure-ground segregation. Finally, dispersion in inter-areal far projections destroys coherence of /spl gamma/ signals, but preserves their amplitude modulations. In conclusion, we propose that the hypothesis of associative processing by /spl gamma/ synchronization be extended to more general forms of signal coupling.

Gain Mechanisms for Contextually Guided Visuomotor Transformations

A prevailing question in sensorimotor research is the integration of sensory signals with abstract behavioral rules (contexts) and how this results in decisions about motor actions. We used neural network models to study how context-specific visuomotor remapping may depend on the functional connectivity among multiple layers. Networks were trained to perform different rotational visuomotor associations, depending on the stimulus color (a nonspatial context signal). In network I, the context signal was propagated forward through the network (bottom-up), whereas in network II, it was propagated backwards (top-down). During the presentation of the visual cue stimulus, both networks integrate the context with the sensory information via a mechanism similar to the classic gain field. The recurrence in the networks hidden layers allowed a simulation of the multimodal integration over time. Network I learned to perform the proper visuomotor transformations based on a context-modulated memory of the visual cue in its hidden layer activity. In network II, a brief visual response, which was driven by the sensory input, is quickly replaced by a context-modulated motor-goal representation in the hidden layer. This happens because of a dominant feedback signal from the output layer that first conveys context information, and then, after the disappearance of the visual cue, conveys motor goal information. We also show that the origin of the context information is not necessarily closely tied to the top-down feedback. However, we suggest that the predominance of motor-goal representations found in the parietal cortex during context-specific movement planning might be the consequence of strong top-down feedback originating from within the parietal lobe or from the frontal lobe.

Planning Movements in Visual and Physical Space in Monkey Posterior Parietal Cortex

Neurons in the posterior parietal cortex respond selectively for spatial parameters of planned goal-directed movements. Yet, it is still unclear which aspects of the movement the neurons encode: the spatial parameters of the upcoming physical movement (physical goal), or the upcoming visual limb movement (visual goal). To test this, we recorded neuronal activity from the parietal reach region while monkeys planned reaches under either normal or prism-reversed viewing conditions. We found predominant encoding of physical goals while fewer neurons were selective for visual goals during planning. In contrast, local field potentials recorded in the same brain region exhibited predominant visual goal encoding, similar to previous imaging data from humans. The visual goal encoding in individual neurons was neither related to immediate visual input nor to visual memory, but to the future visual movement. Our finding suggests that action planning in parietal cortex is not exclusively a precursor of impending physical movements, as reflected by the predominant physical goal encoding, but also contains spatial kinematic parameters of upcoming visual movement, as reflected by co-existing visual goal encoding in neuronal spiking. The co-existence of visual and physical goals adds a complementary perspective to the current understanding of parietal spatial computations in primates.

A cage-based training, cognitive testing and enrichment system optimized for rhesus macaques in neuroscience research

In neurophysiological studies with awake non-human primates (NHP), it is typically necessary to train the animals over a prolonged period of time on a behavioral paradigm before the actual data collection takes place. Rhesus monkeys (Macaca mulatta) are the most widely used primate animal models in system neuroscience. Inspired by existing joystick- or touch-screen-based systems designed for a variety of monkey species, we built and successfully employed a stand-alone cage-based training and testing system for rhesus monkeys (eXperimental Behavioral Intrument, XBI). The XBI is mobile and easy to handle by both experts and non-experts; animals can work with only minimal physical restraints, yet the ergonomic design successfully encourages stereotypical postures with a consistent positioning of the head relative to the screen. The XBI allows computer-controlled training of the monkeys with a large variety of behavioral tasks and reward protocols typically used in systems and cognitive neuroscience research.

Sensorimotor Learning Biases Choice Behavior: A Learning Neural Field Model for Decision Making

According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subjects learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations.

Fully Implantable Multi-Channel Measurement System for Acquisition of Muscle Activity

This paper presents intramuscular electromyogram (EMG) signals obtained with a fully implantable measurement system that were recorded during goal directed arm movements. In a first implantation thin film electrodes were epimysially implanted on the deltoideus of a rhesus macaque and the encapsulation process was monitored by impedance measurements. Increase of impedance reached a constant level after four weeks indicating a complete encapsulation of electrodes. EMG recorded with these electrodes yielded a signal-to-noise ratio of about 80 dB at 200 Hz. The EMG recorded during goal-directed arm movements showed a high similarity to movements in the same direction and at the same time presented clear differences between different movement directions in time domain. Six classifiers and seven time and frequency domain features were investigated with the aim of discriminating the direction of arm movement from EMG signals. Reliable recognition of arm movements was achieved for a subset of the movements under investigation only. A second implantation of the whole measurement system for nine weeks demonstrated simple handling during surgery and good biotolerance in the animals.

Scale-invariance of receptive field properties in primary visual cortex

BackgroundOur visual system enables us to recognize visual objects across a wide range of spatial scales. The neural mechanisms underlying these abilities are still poorly understood. Size- or scale-independent representation of visual objects might be supported by processing in primary visual cortex (V1). Neurons in V1 are selective for spatial frequency and thus represent visual information in specific spatial wavebands. We tested whether different receptive field properties of neurons in V1 scale with preferred spatial wavelength. Specifically, we investigated the size of the area that enhances responses, i.e., the grating summation field, the size of the inhibitory surround, and the distance dependence of signal coupling, i.e., the linking field.ResultsWe found that the sizes of both grating summation field and inhibitory surround increase with preferred spatial wavelength. For the summation field this increase, however, is not strictly linear. No evidence was found that size of the linking field depends on preferred spatial wavelength.ConclusionOur data show that some receptive field properties are related to preferred spatial wavelength. This speaks in favor of the hypothesis that processing in V1 supports scale-invariant aspects of visual performance. However, not all properties of receptive fields in V1 scale with preferred spatial wavelength. Spatial-wavelength independence of the linking field implies a constant spatial range of signal coupling between neurons with different preferred spatial wavelengths. This might be important for encoding extended broad-band visual features such as edges.