Sensory Instruction Research Articles

FN400 and LPC Responses to Different Degrees of Sensory Involvement: A Study of Sentence Comprehension.

The current study tested the likely effect of sensory involvement on the FN400 and late positive complex (LPC) responses to semantic and pragmatic comprehension of English sentences. Fifteen English language learners took part in the event-related potential (ERP) experiment and determined the acceptability of 432 sentences under congruent, semantically incongruent, and pragmatically incongruent conditions. Prior to the ERP recording, the subjects received different sensory instructions for six vocabulary items about which they had no previous knowledge. No sensory instruction was given for three extra words, and these served as the control group. The behavioral data corroborated that integration of more senses in instruction improved learners’ pragmatic comprehension. The ERP data revealed that full sensory involvement (involvement) reduced the FN400 amplitude, facilitating real world knowledge retrieval and pragmatic comprehension. The LPC responses to semantic comprehension showed that learners reanalyzed the sentences instructed through limited sensory involvement (exvolvement) more deeply.

Utilizing High-Density Electroencephalography and Motion Capture Technology to Characterize Sensorimotor Integration While Performing Complex Actions.

Studies of sensorimotor integration often use sensory stimuli that require a simple motor response, such as a reach or a grasp. Recent advances in neural recording techniques, motion capture technologies, and time-synchronization methods enable studying sensorimotor integration using more complex sensory stimuli and performed actions. Here, we demonstrate that prehensile actions that require using complex sensory instructions for manipulating different objects can be characterized using high-density electroencephalography and motion capture systems. In 20 participants, we presented stimuli in different sensory modalities (visual, auditory) containing different contextual information about the object with which to interact. Neural signals recorded near motor cortex and posterior parietal cortex discharged based on both the instruction delivered and object manipulated. Additionally, kinematics of the wrist movements could be discriminated between participants. These findings demonstrate a proof-of-concept behavioral paradigm for studying sensorimotor integration of multidimensional sensory stimuli to perform complex movements. The designed framework will prove vital for studying neural control of movements in clinical populations in which sensorimotor integration is impaired due to information no longer being communicated correctly between brain regions (e.g. stroke). Such a framework is the first step towards developing a neural rehabilitative system for restoring function more effectively.

Neuromodulatory control of localized dendritic spiking in critical period cortex.

Sensory experience in early postnatal life, during so-called critical periods, restructures neural circuitry to enhance information processing. It is unclear why the cortex is susceptible to sensory instruction in early life and why this susceptibility wanes with age. Here, we define a developmentally-restricted engagement of inhibitory circuitry that shapes localized dendritic activity and is needed for vision to drive the emergence of binocular visual responses in mouse primary visual cortex. We find that at the peak of the critical period for binocular plasticity, acetylcholine released from the basal forebrain during periods of heightened arousal directly excites somatostatin-expressing (SST) interneurons. Their inhibition of pyramidal cell dendrites and of fast-spiking, parvalbumin-expressing (PV) interneurons enhances branch-specific dendritic responses and somatic spike rates within pyramidal cells. By adulthood, this cholinergic sensitivity is lost, and compartmentalized dendritic responses are absent but can be re-instated by optogenetic activation of SST cells. Conversely, suppressing SST cell activity during the critical period prevents the normal development of binocular receptive fields by impairing the maturation of ipsilateral eye inputs. This transient cholinergic modulation of SST cells, therefore, appears to orchestrate two features of neural plasticity – somatic disinhibition and compartmentalized dendritic spiking. Loss of this modulation may contribute to critical period closure.

Ears-on Exhibitions

Between March 2013 and November 2014, the Amsterdam Museum had an installation that enabled visitors to compare a recent soundscape recording of the Dam Square with simulations of how the Dam sounded in 1895 and 1935. Constructing these simulations involved virtual acoustics software, recordings of historical artifacts, and research into the urban past. This paper critically discusses how the installation was made and received by comparing the acoustic authenticity ideal behind it with the aims of the early music movement. It concludes by reviewing alternative ways of using sound in history museums by reflecting on issues of framing, identification, sensory instruction, and embodiment.

Effects of memory training or task design? A Commentary on "Neural evidence for the use of digit-image mnemonic in a superior memorist: an fMRI study".

Mathematical experts generally fall in two broad categories: they may be individuals gifted with specific skills, but with deficits in social or other intellectual domains (savants) (Treffert, 2009), or people with mathematical and memory abilities within the normal range, who devote significant amounts of time and energy in practicing specific problems (e.g., memorizing digit sequences, practicing calendrical calculations). Importantly, they can be highly idiosyncratic in their problem solving approaches, and their exceptional abilities in maths do not generalize in other cognitive domains. Yin et al. in this issue offer a rare insight of a gifted memorist (CL), who holds the Guinness World Record for reciting 67,890 digits of π since 2005 (Yin et al., 2015). Building on behavioral data from CL collected in 2006, the current study presents imaging data that shed light on the effects of the memory training on CL's brain networks several years after his intense preparation for breaking the record. CL is a strategy memorizer who encodes two-digit groups as images (fixed associations for numbers 0–99, based on number shape or phonemic encoding, see Table 1A in Hu and Ericsson, 2012), and creates vivid stories with associations that connect them to each other and/or to physical locations (Hu and Ericsson, 2012). In spite of his exceptional memory for digits in π, he has average visual digit span memory (Hu et al., 2009). Crucially, the behavioral tasks employed by Yin et al. were designed to keep CL's performance similar to that of control participants, and do not tap into his ability for serial information memorization. Although CL's accuracy performance in memorizing six two-digit numbers (study phase), and then judging which of two appeared earlier (recall phase) was indistinguishable from that of the control group, fMRI data revealed neural differences during study and recall for CL relative to controls. Specifically, during the encoding phase, bilateral frontal poles, left superior parietal lobule, left premotor cortex, insula, and left dorsolateral prefrontal cortex were more active compared to controls, while left middle and inferior frontal gyrus were less active. During the recall phase, there was higher activity in frontal, parietal and visual areas for CL relative to controls. The authors highlight the finding of frontal pole engagement in CL in the two-digit study and recall conditions and interpret it in terms of retrieval of the practiced digit-image associations. However, based on results from single unit and lesion experiments, one would not expect the pair associates to be represented in prefrontal (Rainer et al., 1999; Sigala et al., 2008), but rather in temporal cortex areas (Miyashita, 1988; Takeda et al., 2005). Prefrontal areas though are important for top-down modulation of posterior sensory and memory areas (Hasegawa et al., 1998; Hon et al., 2009). Crucially, the frontopolar (FP) engagement in the two-digit task was also found in control participants during the recall phase. Perhaps then the FP activation is not best explained by the digit-image mnemonic training, but by the fact that the task required holding the study phase information in working memory and making self-generated decisions in the recall phase, in agreement with FP cell activity patterns reported by Tsujimoto et al. (2010). Unlike neurons in other prefrontal areas, FP cells specifically encode goals that require synthesis of sensory instruction and cognitive processing, and monitor the current status of each goal, e.g., as completed or impending (Tsujimoto et al., 2011). The participants in Yin et al. not only needed to maintain the serial order of the two-digits presented, but also had to judge which digits appeared earlier twice in the recall phase. This required them to keep the digit order and two judgment goals in mind at the same time, before they had to study a new array of six two-digit numbers a few seconds later. Overall, given the rarity of the data from such unique individuals and their quirky approaches to problem solving, it is useful to have neural evidence that intense training changes brain network recruitment even in the context of different tasks and is evident several years after the training intensity has eased. It would be ideal to complement the univariate analysis with a multivariate approach (e.g., Minati and Sigala, 2013). In this recent study of an expert calculator, a multivariate analysis (graph-based mapping of effective connectivity), but not the univariate analysis, showed distinct cortical hubs in occipital and temporal areas involved in processing well-practiced problems. In contrast, hubs in frontal areas (prefrontal, orbitofrontal, and anterior cingulate) were associated with processing less-practiced problems. This combination overcomes the limitations inherent in the localization approaches, and offers insights in the network architecture and neural context within these cognitive processes take place, as well as in the problem solving strategies used by experts.

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.

Emergence of Novel Representations in Primary Motor Cortex and Premotor Neurons during Associative Learning

Neurons in the motor areas of cortex play a key role in associating sensory instructions with movements. However, their ability to acquire and maintain representations of novel stimulus features, especially when these features are behaviorally relevant, remains unknown. We investigated neuronal changes in these areas during and after associative learning, by training monkeys on a novel reaching task that required associating target colors with movement directions. Before and after learning, the monkeys performed a well known center-out task. We found that during learning, up to 48% of the neurons developed learning-related responses, differentiating between the associative task and the center-out task, although movement kinematics were the same. After learning, on returning to the center-out task in which color was irrelevant, many of these neurons maintained their response to the associative task; they displayed novel sensitivity to the color of the target that was relevant during learning. These neuronal responses prevailed in both the primary motor cortex and the ventral and dorsal premotor cortices, without degrading the information that the neurons firing carried about movement direction. Our results show that motor cortical neurons can rapidly develop and maintain sensitivities to novel arbitrary sensory features such as color, when such features are behaviorally relevant.

To Touch or Not to Touch: Posterior Parietal Cortex and Voluntary Behavior

The primate posterior parietal cortex has been implicated in a large number of cognitive functions. In this issue of Neuron, Cui and Andersen show that neurons in this area maintain effector-specific coding of motor intentions without specific sensory instructions and therefore when behavior is chosen by the animal freely.

Tactile sensing-processing: Interface-cover geometry and the inverse-elastic problem

The skin-like elastic cover of a tactile-sensor array plays a fundamental role in determining how the sensor is responding to an arbitrary surface stimulus. Indeed, this cover is the first spatial–temporal sensory instruction in a tactile cellular wave-computer, or in living, neural-tactile signal-processing organs. While the sensor under the elastic layer measures the local strain/stress, we are interested in the stimulating force distribution at the contacting surface. This paper deals with the described inverse problem in the stationary case over a three-axial tactile-sensor array, measuring three components of the local strain tensor of the elastic cover. Our goal here is to design an interface flexible cover to enhance specific capabilities, sensitivity and accuracy, when using the three-axial sensor array. First, on the simplest, flat rubber surface, we create a kind of tactile hyper-accuracy by giving a simple analytical solution to the case when the cover is indented by an arbitrary point load. Second, instead of generalizing our solution to more complex indentation profiles, we try to abolish the need for the complex inverse solution by specifying our cover's geometry and thus reducing the complexity of the sensor's coding mechanism. We create hemispherical bumps over the elastic surface and use a finite-element model to show that with the bumps we can localize the (otherwise continuous) input over the taxels and detect normal and shear force components independently. Finally, we confirm our theoretical results with real-time experimental data and use the measurements for sensor calibration and texture classification.

Movement preparation and working memory: a behavioural dissociation.

We can cross temporal sensorimotor contingencies by remembering sensory events or by anticipating motor responses. Here we tested the hypothesis that sensory and motor representations can be accessed according to different temporal dynamics. We predicted that the manipulation of movement representations would lead to a performance independent from the length of a delay interposed between sensory instructions and behavioural responses. Conversely, we expected a delay-dependent performance whenever temporary storage of sensory information was necessary to solve the task. We have measured reaction times and error rate in subjects performing a delayed non-matching to sample task. Task contingencies rather than explicit instructions ensured that either sensory or motor representations were used to cross the delay period on each trial. We tested our hypothesis by manipulating the length of the delays between stimulus presentation and behavioural response. We found that carrying sensory material over temporal gaps affects performance as a non-linear function of time, whereas movement representations remain robust over a wide range of delays. This novel behavioural paradigm might prove effective in dissociating the neural bases of preparatory and mnestic processes in normal human subjects, as well as their disorders in neurological patients.

Learning Arbitrary Visuomotor Associations: Temporal Dynamic of Brain Activity

Primates can give behavioral responses on the basis of arbitrary, context-dependent rules. When sensory instructions and behavioral responses are associated by arbitrary rules, these rules need to be learned. This study investigates the temporal dynamics of functional segregation at the basis of visuomotor associative learning in humans, isolating specific learning-related changes in neurovascular activity across the whole brain. We have used fMRI to measure human brain activity during performance of two tasks requiring the association of visual patterns with motor responses. Both tasks were learned by trial and error, either before (visuomotor control) or during (visuomotor learning) the scanning session. Epochs of tasks performance (∼30 s) were alternated with a baseline period over the whole scanning session (∼50 min). We have assessed both linear and nonlinear modulations in the differential signal between tasks, independently from overall task differences. The performance indices of the visuomotor learning task smoothly converged onto the values of a steady-state control condition, according to nonlinear timecourses. Specific visuomotor learning-related activity has been found over a distributed cortical network, centred on a temporo-prefrontal circuit. These cortical time-modulated activities were supported early in learning by the hippocampal/parahippocampal complex, and late in learning by the basal ganglia system. These findings suggest the inferior temporal and the ventral prefrontal cortex are critical neural nodes for integrating perceptual information with executive processes.

Premotor cortex of rhesus monkeys: set-related activity during two conditional motor tasks

We compared set-related premotor cortex activity in two conditional motor tasks. In both tasks, a rhesus monkey moved its forelimb to one of two possible targets on the basis of visuospatial instruction stimuli. One target was located to the left of the limb's starting position, the other to the right. In the directional task, a white light situated within the target provided the instruction. In the arbitrary task, colored instruction stimuli equidistant from the targets established an arbitrary relationship between stimulus and response. One hypothesis about set-related premotor cortex activity is that it contributes to the preparation for limb movement on the basis of sensory instruction stimuli. If set-related activity differed profoundly in the arbitrary and directional tasks, then that hypothesis would be untenable. Out of 403 task-related premotor cortex neurons in two monkeys, 130 neurons showed set-related activity, and we studied 118 cells in detail. The vast majority (81%) of these 118 neurons showed no significant difference between the two tasks in set-related activity. When set-related activity did differ, the greatest activity usually occurred after arbitrary instructions; the opposite being the case for only 5% of our sample. Differences in activity during the two tasks, even when statistically significant, were generally small. The present results accord with the hypothesis that set-related premotor cortex activity reflects aspects of motor preparation.