Nonvisual Motor Training Influences Biological Motion Perception

Visual and verbal learning in a genetic metabolic disorder

Objective:Patients with Parkinson’s disease (PD) commonly show deficits on tests of visuospatial functioning. The Identi-Fi is a new measure of visual organization and recognition composed of two components. The Visual Recognition (VR) subtest asks persons to identify an object that has been broken its pieces and rearranged, akin to the Hooper Visual Organization Test, but using updated and colorful pictures. The Visual Matching (VM) subtest involves showing the same stimuli, but the examinee must select the correct response from among five choices (1 correct and 4 foils), placing greater demand on visuospatial discrimination. Together, the two subtests comprise the Visual Organization Index (VOI), reflecting overall visual processing and organization ability. The present study examined performance on the Identi-Fi in patients with PD and its association with other aspects of cognition.Participants and Methods:Participants were 23 patients with PD (95% male; mean age = 69.7 years [SD = 7.8], range = 47-79) and 12 patients with cognitive concerns (CC) who were intact on neuropsychological testing (excluding consideration of Identi-Fi scores; 50% male, mean age = 71.08 [SD = 6.27], range = 60-78) seen for a neuropsychological evaluation at a large Northeastern medical center. As part of a larger battery, patients completed the Identi-Fi, Trail Making Test (TMT), Category Fluency, Test of Premorbid Functioning (TOPF), and Brief Visuospatial Memory Test, Revised (BVMT-R).Results:The PD group performed significantly worse than the CC group on VR and VM, as well as VOI, of the Identi-Fi (p < .001). Within the PD group, poorer VR, VM, and VOI performance was associated with lower scores on the TOPF (p < .05), BVMT-R learning (p < .05) and delayed recall (p < .05), as well as TMT Parts A and B (p < .05). VR was significantly correlated with Category Fluency (p < .05), while a trend was seen for the association between VOI and Category Fluency (p = .094).Conclusions:Identi-Fi performance was worse in the PD group than the CC group, which is consistent with prior research indicating that visuospatial processing is often abnormal in patients with PD. Furthermore, findings indicate that poorer performance on the Identi-Fi in the PD group is associated with poorer cognitive functioning in other domains (i.e., visuospatial learning and memory, processing speed, cognitive flexibility, and semantic fluency), as well as lower premorbid intellectual functioning. While these findings suggest that the Identi-Fi is useful in identifying visuospatial dysfunction in PD, findings should be interpreted with caution given the small sample sizes and uneven gender distribution

The relationship of novelty preferences during infancy to later intelligence and later recognition memory

To examine age-related differences in auditory speech recognition and visual text recognition performance for parallel sets of stimulus materials in the auditory and visual modalities. In addition, the effects of variation in rate of presentation of stimuli in each modality were investigated in each age group. A mixed-model design was used in which 3 independent groups (13 young adults with normal hearing, 10 elderly adults with normal hearing, and 16 elderly hearing-impaired adults) listened to auditory speech tests (a sentence-in-noise task, time-compressed monosyllables, and a speeded-spelling task) and viewed visual text-based analogs of the auditory tests. All auditory speech materials were presented so that the amplitude of the speech signal was at least 15 dB above threshold through 4000 Hz. Analyses of the group data revealed that when baseline levels of performance were used as covariates in the group analyses the only significant group difference was that both elderly groups performed worse than the young group on the auditory speeded-speech tasks. Analysis of individual data, using correlations, factor analysis, and linear regression, was generally consistent with the group data and revealed significant, moderate correlations of performance for similar tasks across modalities, but stronger correlations across tasks within a modality. This suggests that performance on these tasks was mediated both by a common underlying factor, such as cognitive processing, as well as modality-specific processing. Performance on measures of auditory processing of speech examined here was closely associated with performance on parallel measures of the visual processing of text obtained from the same participants. Young and older adults demonstrated comparable abilities in the use of contextual information in each modality, but older adults, regardless of hearing status, had more difficulty with fast presentation of auditory speech stimuli than young adults. There were no differences among the 3 groups with regard to the effects of presentation rate for the visual recognition of text, at least for the rates of presentation used here.

Animates receive preferential attentional processing over inanimates because, from an evolutionary perspective, animates are important to human survival. We investigated whether animacy affects visual statistical learning—the detection and extraction of regularities in visual information from our rich, dynamic, and complex environment. Participants completed a selective-attention task, in which regularities were embedded in two visual streams, an attended and an unattended visual stream. The attended visual stream always consisted of line-drawings of non-objects, while the unattended visual stream consisted of line-drawings of either animates or inanimates. Participants then completed a triplet-discrimination task, which assessed their ability to extract regularities from the attended and unattended visual streams. We also assessed participants’ awareness of regularities in the visual statistical learning task, and asked if any learning strategies were used. We were specifically interested in whether the animacy status of line-drawings in the unattended visual stream would affect visual statistical learning. There were four key findings. First, selective attention modulates visual statistical learning, with greater visual statistical learning for attended than for unattended information. Second, animacy does not affect visual statistical learning, with no differences found in visual statistical learning performance between the animate and inanimate condition. Third, awareness of regularities was associated with visual statistical learning of attended information. Fourth, participants used strategies (e.g., naming or labelling stimuli) during the visual statistical learning task. Further research is required to understand whether visual statistical learning is one of the adaptive functions that evolved from ancestral environments.

Temporal perceptual learning shows specificity to the visual or auditory modality, or asymmetric partial transfer from auditory to visual, but not vice versa. These findings are interpreted as evidence for distributed, rather than central, temporal processing (Ivry & Schlerf, 2008). For visual perceptual learning, location and orientation specificity can be eliminated with double training, indicating that learning specificity may not be used to infer the mechanisms of perceptual learning (e.g., Xiao et al., 2008). Here we investigated whether double training can eliminate the modality specificity in temporal learning. We first replicated asymmetric partial transfer results between auditory and visual learning of a temporal-interval discrimination (TID) task with standard training. The standard interval was marked by a pair of auditory beeps or visual gratings at 100-ms. The subjects practiced either the auditory or the visual TID task for 5 sessions. Visual TID learning had no impact on auditory TID performance (p=0.65), while auditory TID learning improved visual TID performance (p=0.005), although not as much as direction visual TID learning (p=0.028). However, complete learning transfer was evident with double-training. When visual TID learning was paired with an auditory frequency discrimination task at the same 100-ms interval, auditory TID performance was improved similarly to direct auditory training (p=0.051), indicating complete cross-modal learning transfer. Similarly, when auditory TID learning was paired with a visual contrast discrimination task at the same 100-ms interval, visual TID performance was improved equally as direct visual training (p=0.95), again indicating complete cross-modal learning transfer. In both cases we found no significant impact of practicing auditory frequency discrimination or visual contrast discrimination alone on TID performance. Our results suggest mutual and nearly complete learning transfer of TID learning between visual and auditory modalities, which are consistent with a central temporal processing mechanism shared by different modalities.

The lack of labeled data presents a common challenge in many computer vision and machine learning tasks. Semisupervised learning and transfer learning methods have been developed to tackle this challenge by utilizing auxiliary samples from the same domain or from a different domain, respectively. Self-taught learning, which is a special type of transfer learning, has fewer restrictions on the choice of auxiliary data. It has shown promising performance in visual learning. However, existing self-taught learning methods usually ignore the structure information in data. In this paper, we focus on building a self-taught coding framework, which can effectively utilize the rich low-level pattern information abstracted from the auxiliary domain, in order to characterize the high-level structural information in the target domain. By leveraging a high quality dictionary learned across auxiliary and target domains, the proposed approach learns expressive codings for the samples in the target domain. Since many types of visual data have been proven to contain subspace structures, a low-rank constraint is introduced into the coding objective to better characterize the structure of the given target set. The proposed representation learning framework is called self-taught low-rank (S-Low) coding, which can be formulated as a nonconvex rank-minimization and dictionary learning problem. We devise an efficient majorization-minimization augmented Lagrange multiplier algorithm to solve it. Based on the proposed S-Low coding mechanism, both unsupervised and supervised visual learning algorithms are derived. Extensive experiments on five benchmark data sets demonstrate the effectiveness of our approach.

Our previous study exploring the use of an Audience Response System (ARS) to promote active learning and group interactivity in a medical school histology laboratory determined the method to be effective in stimulating discussion, enhancing peer interaction, and applying the material. Separately, the instructional strategy known as Peer Instruction (PI) provides a model for student interaction using a controlled questioning process. Upon implementation of PI, published studies report increases in students’ conceptual reasoning and quantitative problem solving skills. Our study seeks to further develop the concept of ARS in a histology course by implementing the use of PI in a medical histology laboratory setting.Presenting clinically‐relevant questions associated with microscope images using the PI model provides a system through which visual learning, pattern recognition, group interaction, and clinical application are simultaneously addressed. The benefits of Peer Instruction Laboratory Sessions (PILS) are evaluated by obtaining individual student assessments from the PILS using ARS data and comparing them to corresponding student laboratory exam scores. This data comparison thus helps to quantify the impact of PILS on visual application and long term material retention.

We introduced haptic cues to the serial reaction time (SRT) task alongside the standard visual cues to explore the relative contributions of haptic and visual cues to motor memory and perceptual memory. Motor learning is a complex process that likely depends on the availability of haptic sensory feedback. Motor learning is also often an implicit process, wherein the learner is not even aware that learning is taking place. The SRT task was devised to study implicit learning. Reaction times (RTs) are reduced with practice even in the absence of explicit learning about a sequence embedded in a train of cues. We adopted an SRT protocol developed by Willingham in 1999 to determine whether haptic cues contribute differently than visual cues to the balance of motor and perceptual learning. Experimental results involving 32 participants showed that sequence learning occurs implicitly with haptic stimuli to much the same extent as visual stimuli. Also, it was revealed that the dependence on motor memory (as opposed to perceptual memory) was greater in the group responding to haptic cues than the group responding to visual cues. Comparing the dependence on motor versus perceptual memory, the haptic group reached marginal significance (p=.09), whereas the visual group difference was not significant (p=.23).

We have been investigating motor control and learning in parkinsonian subjects. In the current study, we sought to explore the existence of deficits in procedural motor learning, which is a form of implicit motor learning where skill improves over repetitive blocks of trials. We sought to determine, in particular, whether any such deficit is accentuated during specific types or phases of learning. We would expect that those specific learning tasks would require the greatest participation of the basal ganglia. Numerous studies have found that Parkinson's disease (PD) patients may show deficits in learning. Combined with information about basal ganglia neuronal connections and activity, this led some investigators to suggest that one of the key functions of the basal ganglia is to facilitate learning. To investigate these learning deficits, we used a robotic device to generate conservative force fields that disturbed the subjects' arm movements, thereby generating a "virtual mechanical environment" that subjects learned to manipulate. Movements were successively grouped into blocks comprising five different conditions: motor performance, early learning, late learning, negative transfer, and aftereffect motor performance. Our results with eight right-handed PD subjects and nine age-matched controls showed a relative decrease in the rate of learning for the PD patients in all blocks, but greater differences emerged between groups during novelty phases of learning. In particular, the difference in performance during the negative transfer condition reached statistical significance, suggesting that the basal ganglia might be a key center for "switching" motor patterns. Our results support the hypothesis that deficiencies in procedural motor learning are characteristic of PD. They add to existing evidence which has suggested a key role for the basal ganglia when new sensorimotor mappings are required by novel task environments. Better understanding of these deficits should facilitate the rehabilitation of PD patients.

Visual recognition is the most critical function of a harvesting robot, and the accuracy of the harvesting action is based on the performance of visual recognition. However, unstructured environment, such as severe occlusion, fruits overlap, illumination changes, complex backgrounds, and even heavy fog weather, pose series of serious challenges to the detection accuracy of the recognition algorithm. Hence, this paper proposes an improved YOLO v4 model, called YOLO v4+, to cope with the challenges brought by unstructured environment. The output of each Resblock_body in the backbone is processed using a simple, parameterless attention mechanism for full dimensional refinement of extracted features. Further, in order to alleviate the problem of feature information loss, a multi scale feature fusion module with fusion weight and jump connection structure was pro-posed. In addition, the focal loss function is adopted and the hyperparameters α, γ are adjusted to 0.75 and 2. The experimental results show that the average precision of the YOLO v4+ model is 94.25% and the F1 score is 93%, which is 3.35% and 3% higher than the original YOLO v4 respectively. Compared with several state-of-the-art detection models, YOLO v4+ not only has the highest comprehensive ability, but also has better generalization ability. Selecting the corresponding augmentation method for specific working condition can greatly improve the model detection accuracy. Applying the proposed method to harvesting robots may enhance the applicability and robustness of the robotic system.

The primate visual system is often described as a hierarchical feature-conjunction pathway, whereby each level represents an increasingly complex combination of image elements, culminating in the representation of whole coherent images in anterior inferior temporal cortex. Although many models of the ventral visual stream emphasize serial feedforward processing ((Poggio T, Mutch J, Leibo J, Rosasco L, Tacchetti A. The computationalmagic of the ventral stream: sketch of a theory (and why some deep architectures work). TechRep MIT-CSAIL-TR-2012-035. MIT CSAIL, Cambridge, MA. 2012); (Yamins DLK, DiCarlo JJ. Eight open questions in the computational modeling of higher sensory cortex. Curr Opin Neurobiol. 2016:37:114-120.)), anatomical studies show connections that bypass intermediate areas and that feedback to preceding areas ((Distler C, Boussaoud D, Desimone R, Ungerleider LG. Cortical connections of inferior temporal area TEO in macaque monkeys. J Comp Neurol. 1993:334(1):125-150.); (Kravitz DJ, Saleem KS, Baker CI, Mishkin M. A new neural framework for visuospatial processing. Nat Rev Neurosci. 2011:12(4):217-230.)). Prior studies on visual discrimination and object transforms also provide evidence against a strictly feed-forward serial transfer of information between adjacent areas ((Kikuchi R, Iwai E. The locus of the posterior subdivision of the inferotemporal visual learning area in the monkey. Brain Res. 1980:198(2):347-360.); (Weiskrantz L, Saunders RC. Impairments of visual object transforms in monkeys. Brain. 1984:107(4):1033-1072.); (Kar K, DiCarlo JJ. Fast recurrent processing via ventrolateral prefrontal cortex is needed by the primate ventral stream for robust Core visual object recognition. Neuron. 2021:109(1):164-176.e5.)). Thus, we sought to investigate whether behaviorally relevant propagation of visual information is as strictly sequential as sometimes supposed. We compared the accuracy of visual recognition after selective removal of specific subregions of inferior temporal cortex-area TEO, area TE, or both areas combined. Removal of TEO alone had no detectable effect on recognition memory, whereas removal of TE alone produced a large and significant impairment. Combined removal of both areas created no additional deficit relative to removal of TE alone. Thus, area TE is critical for rapid visual object recognition, and detailed image-level visual information can reach area TE via a route other than through TEO.

Aphantasia and prosopagnosia are both rare conditions with impairments in visual cognition. While prosopagnosia refers to a face recognition deficit, aphantasics exhibit a lack of mental imagery. Current object recognition theories propose an interplay of perception and mental representations, making an association between recognition performance and visual imagery plausible. While the literature assumes a link between aphantasia and prosopagnosia, other impairments in aphantasia have been shown to be rather global. Therefore, we assumed that aphantasics do not solely exhibit impairments in face recognition but rather in general visual recognition performance, probably moderated by stimulus complexity. To test this hypothesis, 65 aphantasics were compared to 55 controls in a face recognition task, the Cambridge Face Memory Test, and a corresponding object recognition task, the Cambridge Car Memory Test. In both tasks, aphantasics performed worse than controls, indicating mild recognition deficits without face-specificity. Additional correlations between imagery vividness and performance in both tasks were found, suggesting that visual imagery influences visual recognition not only in imagery extremes. Stimulus complexity produced the expected moderation effect but only for the whole imagery-spectrum and only with face stimuli. Overall, the results imply that aphantasia is linked to a general but mild deficit in visual recognition.

Does visual recognition entail verifying an idea about what is perceived? This question was addressed in the three studies of this thesis. The main hypothesis underlying the investigation was that visual recognition is an active process involving hypothesis testing. Recognition of faces (Study 1), scenes (Study 2) and objects (Study 3) was investigated using eye movement registration as a window on the recognition process. In Study 1, a functional relationship between eye movements and face recognition was established. Restricting the eye movements reduced recognition performance. In addition, perceptual reinstatement as indicated by eye movement consistency across study and test was related to recollective experience at test. Specifically, explicit recollection was related to higher eye movement consistency than familiarity-based recognition and false rejections (Studies 1-2). Furthermore, valid expectations about a forthcoming stimulus scene produced eye movements which were more similar to those of an earlier study episode, compared to invalid expectations (Study 2). In Study 3 participants recognized fragmented objects embedded in nonsense fragments. Around 8 seconds prior to explicit recognition, participants began to fixate the object region rather than a similar control region in the stimulus pictures. Before participants’ indicated awareness of the object, they fixated it with an average of 9 consecutive fixations. Hence, participants were looking at the object as if they had recognized it before they became aware of its identity. Furthermore, prior object information affected eye movement sampling of the stimulus, suggesting that semantic memory was involved in guiding the eyes during object recognition even before the participants were aware of its presence. Collectively, the studies support the view that gaze control is instrumental to visual recognition performance and that visual recognition is an interactive process between memory representation and information sampling.

Despite its economic and ecological importance, little is known about the learning abilities of the South American bumblebee Bombus pauloensis. To date, no studies have explored the visual learning capacity of its foragers, potential differences between non-pollen and pollen foragers, the effect of body size on learning, or male learning abilities. Here, we investigated the visual learning performance of workers, taking into account forager type (pollen versus non-pollen foragers) and body size. As a complementary analysis, we assessed the same variables in males. Our results show that both female foragers and males of this South American bumblebee can learn to associate a specific color with a sugar reward and do not exhibit color bias for the tested colors (blue and yellow). We found no significant differences in color learning ability or body size between pollen and non-pollen foragers. Additionally, body size significantly influenced visual learning performance during the testing phase. This study provides new insights into the visual learning abilities of both foragers and males in the South American bumblebee Bombus pauloensis, enriching the understanding of cognition of native pollinators.