Target Discrimination Research Articles

Adaptive Max-Margin One-Class Classifier for SAR Target Discrimination in Complex Scenes

Synthetic aperture radar (SAR) target discrimination is an important stage that distinguishes targets from clutters in the radar automatic target recognition field. However, in complex SAR scenes, the performance of some traditional discriminators will degrade. As an effective tool for one-class classification (OCC), the max-margin one-class classifier has attracted much attention for SAR target discrimination, as it can effectively reduce the impact of multiple clutters. However, the performance of the max-margin one-class classifier is very sensitive to the values of kernel parameters. To solve the problem, this paper proposes an adaptive max-margin one-class classifier for SAR target discrimination in complex scenes. In a max-margin one-class classifier with a suitable kernel parameter, the distance between a sample and classification boundary satisfies a certain geometric relationship, i.e., edge samples in input space are transformed to the region in the kernel space close to boundary, while interior samples in input space are transformed to the region in the kernel space far away from boundary. Therefore, we define the information entropy of samples in the kernel space to measure the distance between samples and classification boundary. To automatically obtain the optimal kernel parameter of the max-margin one-class classifier, the edge and interior samples in the input space are first selected, and then the parameter optimization is performed by minimizing information entropy of interior samples and simultaneously maximizing the information entropy of edge samples. Experimental results of the synthetic datasets and measured synthetic aperture radar (SAR) datasets validate the effectiveness of our method.

Spatiotemporal Dynamics of Covert Attention With Different Degrees of Central Visual Field Defects: An ERP and sLORETA Study.

PurposeThe present study aimed to investigate the spatiotemporal dynamics of covert attention by simulating different degrees of central visual field defects in healthy subjects.MethodsAn electroencephalogram (EEG) was recorded while 40 normal-sighted subjects performed a target discrimination task. Target stimuli simulated different defect degrees of the central visual field by artificially central scotomas (5, 10, 20, and 30 degrees of visual angle) masked on the center of black-and-white checkerboards. Event-related potentials (ERPs) and standardized low-resolution brain electromagnetic tomography (sLORETA) based on ERPs were analyzed.ResultsERP results indicated that during early perceptual processes, compared with 5-degree and 10-degree defects, N1 amplitudes of 20-degree and 30-degree defects decreased, whereas P2 amplitudes significantly reduced in 30-degree defects. During later discrimination and decision processing, N2 amplitudes gradually increased from 5-degree to 30-degree defects, whereas P3 amplitudes gradually decreased. Source localization indicated that 5-degree and 10-degree defects had stronger activations than 20-degree and 30-degree defects from the occipital cortex to the ventral stream and dorsal streams. Especially, 30-degree defects primarily recruited additional activations in the ventrolateral prefrontal cortex and ventral stream and later caused the disconnection of dorsolateral prefrontal-posterior parietal cortices in the dorsal stream.ConclusionsDifferent degrees of central visual field defects differed in distinct spatiotemporal characteristics at multiple stages of covert attention, from top-down forward feedback and attentional allocation to executive controls through ventral and dorsal processing streams, suggesting that the combination of ERP and source localization can reveal the spatiotemporal control capacity of the cortex on central visual field defects.

Periodic attention operates faster during more complex visual search

Attention has been found to sample visual information periodically, in a wide range of frequencies below 20 Hz. This periodicity may be supported by brain oscillations at corresponding frequencies. We propose that part of the discrepancy in periodic frequencies observed in the literature is due to differences in attentional demands, resulting from heterogeneity in tasks performed. To test this hypothesis, we used visual search and manipulated task complexity, i.e., target discriminability (high, medium, low) and number of distractors (set size), while electro-encephalography was simultaneously recorded. We replicated previous results showing that the phase of pre-stimulus low-frequency oscillations predicts search performance. Crucially, such effects were observed at increasing frequencies within the theta-alpha range (6–18 Hz) for decreasing target discriminability. In medium and low discriminability conditions, correct responses were further associated with higher post-stimulus phase-locking than incorrect ones, in increasing frequency and latency. Finally, the larger the set size, the later the post-stimulus effect peaked. Together, these results suggest that increased complexity (lower discriminability or larger set size) requires more attentional cycles to perform the task, partially explaining discrepancies between reports of attentional sampling. Low-frequency oscillations structure the temporal dynamics of neural activity and aid top-down, attentional control for efficient visual processing.

Hyperspectral Band Selections for Enhancing the Discrimination of Difficult Targets Using Local Band Index and Particle Swarm Optimization

Due to their similar color and material variability, some ground objects have similar characteristics and overlap in some bands. This leads to a drop in the classification accuracy of hyperspectral images. To address this problem, we simulated hyperspectral images of vegetation and objects with similar colors by mixed pixel calculation to test the classification performance of the dimensionality reduction method for samples with close spectra. In addition, we proposed a novel wavelength selection algorithm called the LBI-BPSO (Binary Particle Swarm Optimization with Local Band Index), which combines the information amount and inter-class separability. The novelty of this study is in its proposal of an improvement of IOIF using inter-class distance. Based on the calculation of the information content by the local band index, the inter-class distance was introduced to measure the inter-class separability of ground objects, and a reasonable fitness function is proposed. It can obtain the wavelength combination of two DR criteria, which considers the larger amount of information and better sample separability. The classification performance of the simulation dataset is verified by comparing LBI-BPSO with Partitioned Relief-F, IOIF (Improved Optimum Index Factor) and GA-BPSO (Particle Swarm Optimization with a Genetic Algorithm). Under the conditions that the signal-to-noise ratio is 1000, compared with IOIF, the OA of LBI-BPSO improved by 2.90%, the AA improved by 2.75%, and the Kappa coefficient improved by 3.91%. LBI-BPSO also showed the best results in the analysis of different abundances and signal-to noise-ratios. The results show that the new wavelength selection algorithm LBI-BPSO, which combines the amount of information and inter-class separability, is more effective than IOIF and GA-BPSO in classifying objects with similar colors and effectively improves the classification accuracy.

Is broad angular coverage necessary for echolocation-based discrimination involving aspect-dependent targets?

Building on the foundation of Dr. Whitlow Au’s pioneer and extensive work on the sonar of dolphins, recent research has illuminated the dynamic nature of echolocation involving free-swimming toothed whales. The sophisticated orchestration of movements and biosonar outputs by toothed whales is particularly relevant in the context of developing agile autonomous sonar-guided underwater vehicles. In this study, we test the hypothesis that broad angular coverage, which provide comprehensive echo information of aspect-dependent objects, is necessary for target discrimination via echolocation. We trained a harbor porpoise to actively approach and select a sphere against a spheroid in a two-alternative forced-choice target discrimination task in a net pan. Two spheroids of different aspect ratios representing two overall difficulty levels were used with each presented at diverse orientations when paired with the sphere. We show that the porpoise can discriminate these targets without acquiring aspect-dependent spheroid echo information over broad ranges of angles. Instead, focused, rapid sampling via buzzes appears to aid discrimination in more challenging scenarios. These results suggest that echolocation-based discrimination involving aspect-dependent objects is possible based on subsets of echo signatures without more extensive angular sampling that could build toward an understanding of the target identity. [Work supported by ONR.]

Loop-Mediated Isothermal Amplification for Detection of Plant Pathogens in Wheat (Triticum aestivum).

Wheat plants can be infected by a variety of pathogen species, with some of them causing similar symptoms. For example, Zymoseptoria tritici and Parastagonospora nodorum often occur together and form the Septoria leaf blotch complex. Accurate detection of wheat pathogens is essential in applying the most appropriate disease management strategy. Loop-mediated isothermal amplification (LAMP) is a recent molecular technique that was rapidly adopted for detection of plant pathogens and can be implemented easily for detection in field conditions. The specificity, sensitivity, and facility to conduct the reaction at a constant temperature are the main advantages of LAMP over immunological and alternative nucleic acid-based methods. In plant pathogen detection studies, LAMP was able to differentiate related fungal species and non-target strains of virulent species with lower detection limits than those obtained with PCR. In this review, we explain the amplification process and elements of the LAMP reaction, and the variety of techniques for visualization of the amplified products, along with their advantages and disadvantages compared with alternative isothermal approaches. Then, a compilation of analyses that show the application of LAMP for detection of fungal pathogens and viruses in wheat is presented. We also describe the modifications included in real-time and multiplex LAMP that reduce common errors from post-amplification detection in traditional LAMP assays and allow discrimination of targets in multi-sample analyses. Finally, we discuss the utility of LAMP for detection of pathogens in wheat, its limitations, and current challenges of this technique. We provide prospects for application of real-time LAMP and multiplex LAMP in the field, using portable devices that measure fluorescence and turbidity, or facilitate colorimetric detection. New technologies for detection of plant pathogen are discussed that can be integrated with LAMP to obtain elevated analytical sensitivity of detection.

A Pilot Randomized Controlled Trial of Goal Management Training in Canadian Military Members, Veterans, and Public Safety Personnel Experiencing Post-Traumatic Stress Symptoms.

Post-traumatic stress disorder (PTSD) is a severe psychiatric illness that disproportionately affects military personnel, veterans, and public safety personnel (PSP). Evidence demonstrates that PTSD is significantly associated with difficulties with emotion regulation (ER) and difficulties with cognitive functioning, including difficulties with attention, working memory, and executive functioning. A wide body of evidence suggests a dynamic interplay among cognitive dysfunction, difficulties with ER, and symptoms of PTSD, where numerous studies have identified overlapping patterns of alterations in activation among neuroanatomical regions and neural circuitry. Little work has examined interventions that may target these symptoms collectively. The primary objective of this pilot randomized controlled trial (RCT) with a parallel experimental design was to assess the effectiveness of goal management training (GMT), a cognitive remediation intervention, in reducing difficulties with cognitive functioning, and to determine its effects on PTSD symptoms and symptoms associated with PTSD, including difficulties with ER, dissociation, and functioning among military personnel, veterans, and PSP. Forty-two military personnel, veterans, and PSP between the ages of 18 and 70 with symptoms of PTSD were recruited across Ontario, Canada between October 2017 and August 2019. Participants were randomized to either the waitlist (WL) (n = 18) or the GMT (n = 22) condition. Participants in both conditions received self-report measures and a comprehensive neuropsychological assessment at baseline, post-intervention, and 3-month follow-up. Following their completion of the 3-month follow-up, participants in the WL condition were given the opportunity to participate in GMT. Assessors and participants were blind to intervention allocation during the initial assessment. A series of 2 (time) × 2 (group) ANOVAs were conducted to assess the differences between the WL and GMT conditions from pre- to post-intervention for the self-report and neuropsychological measures. The results demonstrated significant improvements in measures of executive functioning (e.g., verbal fluency, planning, impulsivity, cognitive shifting, and discrimination of targets) and trending improvements in short-term declarative memory for participants in the GMT condition. Participants in the GMT condition also demonstrated significant improvements from pre- to post-testing in measures of subjective cognition, functioning, PTSD symptom severity, difficulties with ER, dissociative symptom severity, and depression and anxiety symptoms. No adverse effects were reported as a result of participating in GMT. The results of this pilot RCT show promise that GMT may be a useful intervention to improve symptoms of cognitive dysfunction, symptoms of PTSD, and symptoms associated with PTSD within military personnel, veterans, and PSP. Future work is needed to address the small sample size and the durability of these findings.

PlexProbes enhance qPCR multiplexing by discriminating multiple targets in each fluorescent channel.

The probe technology described in this paper facilitates detection and discrimination of multiple targets in a single fluorescent channel during PCR. This provides a strategy for doubling the number of targets that can be analysed simultaneously on existing PCR instruments. These probes are referred to as PlexProbes and produce fluorescence that can be switched ‘on’ or ‘off’ in the presence of target by manipulating the temperature. During PCR, fluorescence can be measured at multiple temperatures allowing discrimination of specific targets at defined temperatures. In a single fluorescent channel, a model duplex assay allowed either real-time or endpoint detection of Chlamydia trachomatis (CT) at 52°C and end-point detection of Neisseria gonorrhoeae (GC) at 74°C. Using this model system, as few as 40 copies of each specific target could be detected as single infection or co-infection, regardless of the presence or absence of the other target. A PlexProbe prototype assay for sexually transmitted infections (PP-STI) which simultaneously enables detection and differentiation of six targets using only three fluorescent channels was then constructed and evaluated. The PP-STI assay detects GC (2 gene targets), CT, Mycoplasma genitalium (MG), Trichomonas vaginalis (TV) and an internal control (IC). To evaluate assay performance, a panel of archived clinical samples (n = 337) were analysed using PP-STI and results compared to those obtained with a commercially available diagnostic assay. The overall agreement between results obtained with the PP-STI assay and the reference test was greater than 99.5%. PlexProbes offer a method of detecting more targets from a single diagnostic test, empowering physicians to make evidence-based treatment decisions while conserving time, labour, sample volume and reagent costs.

C-reactive protein and affective inhibition in bipolar disorder

BackgroundIndividuals with bipolar disorder (BD) experience cognitive and affective processing deficits that often persist beyond the remission of acute mood symptoms. One possible biological mechanism for these deficits involves the potential effects of chronic low-grade peripheral inflammation on brain function. Peripheral inflammation has been associated with reduced executive functioning and memory performance, as well as altered reward processing in BD, but whether it is also implicated in cognitive-affective processing remains unknown. MethodPeripheral inflammation was measured by serum C-reactive protein (CRP) in 119 adults with BD I or II, age 18–65. All participants completed the Affective Go/No-Go Task, a measure of cognitive-emotional processing. Correlations of CRP with discrimination of and response times to Negative, Positive, and Neutral words were performed before and after adjustment for severity of residual depressive symptoms and other demographic and clinical characteristics associated with inflammation. ResultsIncreased CRP was significantly associated with reduced negative target discriminability, which was also significantly reduced compared to positive and neutral target conditions. Additionally, greater CRP was associated with faster response times for both negative hits and commissions, as well as positive commissions. ConclusionsThis study adds to existing research demonstrating associations between inflammation and cognition or reward sensitivity and motivation separately in BD, by raising the possibility that inflammation is also implicated in the integration of cognitive-affective processing. Assessment of these associations over time is warranted to determine involvement of inflammation and cognitive-emotional processing in course of illness and identify critical periods for possible modulation of inflammation.

Model study of target discrimination in concurrent auditory events

With the development of automation technology in human-machine interface, the traditional visual display no longer met the needs of complicated control systems, while auditory display has become an important part of human-machine interface design. Analysing the auditory attention selection behaviours in concurrent auditory events is essential for the design and evaluation of the auditory interface. Listeners tend to pay attention to auditory target with physical attributes which were more salient and informative with deep cognitive level. Listeners tend to focus on the important information in the concurrent auditory events. By combining the two tendencies of the selective attention mechanism, the binary Logit model was built to analyse human auditory selective attention (ASA) behaviour, and the auditory target's selection can be transformed into a probability event. The continuous speech-shaped noise (SSN) was described by the concurrent auditory events scene, which is a typical target discrimination task for ASA. An experiment using the target discrimination task in SSN was conducted to verify the model. The results showed that the listener's attention behaviour was in good agreement with the proposed Logit model. The proposed ASA model is effective and reasonable, which is promising for use in behaviour analysis, auditory display optimization, and interface design.

Attentional signals projecting centrifugally to the avian retina: A dual contribution to visual search

Among vertebrates, birds have a particularly well-developed retinopetal system, i.e., the centrifugal system projecting from the brain to the retina. Primary, secondary and tertiary neurons of the retinopetal system connect serially in a one-to-one-to-one fashion, thereby assembling several thousand retinopetal modules projecting in parallel to the retina. The signal conveyed by the retinopetal system enhances the visual responses of retinal ganglion cells (RGCs), and each retinopetal module may facilitate the RGCs in a topographically restricted area. We investigated how the retinopetal signal contributes to visual search by first training Japanese quail to search and peck a target stimulus presented on one of three touch-sensor monitors around the bird and then examining the effect of retinopetal signal blockage on the task. Our results indicate that the retinopetal signal improves both stimulus detectability and target discriminability. Thus, this study confirms that the avian retinopetal system functions specifically in attentional facilitation of the retina; this new finding suggests that this system benefits early detection and late selection phases of visual search. The fast and precise target detection facilitated by the retinopetal signal may be transformed into quick and correct orienting to the target through visuomotor transformation mechanisms implemented in the optic tectum.

The interplay between audiovisual temporal synchrony and semantic congruency in the cross-modal boost of the visual target discrimination during the attentional blink.

The visual attentional blink can be substantially reduced by delivering a task‐irrelevant sound synchronously with the second visual target (T2), and this effect is further modulated by the semantic congruency between the sound and T2. However, whether the cross‐modal benefit originates from audiovisual interactions or sound‐induced alertness remains controversial, and whether the semantic congruency effect is contingent on audiovisual temporal synchrony needs further investigation. The current study investigated these questions by recording event‐related potentials (ERPs) in a visual attentional blink task wherein a sound could either synchronize with T2, precede T2 by 200 ms, be delayed by 100 ms, or be absent, and could be either semantically congruent or incongruent with T2 when delivered. The behavioral data showed that both the cross‐modal boost of T2 discrimination and the further semantic modulation were the largest when the sound synchronized with T2. In parallel, the ERP data yielded that both the early occipital cross‐modal P195 component (192–228 ms after T2 onset) and late parietal cross‐modal N440 component (424–448 ms) were prominent only when the sound synchronized with T2, with the former being elicited solely when the sound was further semantically congruent whereas the latter occurring only when that sound was incongruent. These findings demonstrate not only that the cross‐modal boost of T2 discrimination during the attentional blink stems from early audiovisual interactions and the semantic congruency effect depends on audiovisual temporal synchrony, but also that the semantic modulation can unfold at the early stage of visual discrimination processing.

A Convolutional Neural Network-Based Method for Discriminating Shadowed Targets in Frequency-Modulated Continuous-Wave Radar Systems.

The radar shadow effect prevents reliable target discrimination when a target lies in the shadow region of another target. In this paper, we address this issue in the case of Frequency-Modulated Continuous-Wave (FMCW) radars, which are low-cost and small-sized devices with an increasing number of applications. We propose a novel method based on Convolutional Neural Networks that take as input the spectrograms obtained after a Short-Time Fourier Transform (STFT) analysis of the radar-received signal. The method discerns whether a target is or is not in the shadow region of another target. The proposed method achieves test accuracy of 92% with a standard deviation of 2.86%.

Three Birds With One Stone: User Intention Understanding and Influential Neighbor Disclosure for Injection Attack Detection

Recommender system, as a data-driven way to help customers locate products that match their interests, is increasingly critical for providing competitive customer suggestions in many web services. However, recommender systems are highly vulnerable to malicious injection attacks due to their fundamental vulnerabilities and openness. With the endless emergence of new attacks, how to provide a feasible way for defending different malicious threats against online recommendations is still an under-explored issue. In this paper, we explore a new way to defend malicious injection attacks through user intention understanding and influential neighbour disclosure. Specifically, we propose a detection approach, termed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TBOS</i> ( <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</u> hree <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</u> irds with <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</u> ne <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</u> tone), to deal with different malicious threats. In <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TBOS</i> , we first develop the discrimination of attack target by combining global influence evaluation and risk attitude estimation of users. In order to make <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TBOS</i> controllable, second, we propose to incorporate an optimal denoising mechanism to remove disturbed information before detection. To enhance the representativeness and predictability of detection model, finally, we propose to leverage a behavioral label propagation mechanism based on constructed label space for the determination of malicious injection behaviors. Extensive experiments on both synthetic and real data demonstrate that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TBOS</i> outperforms all baselines in different cases. Particularly, the detection performance of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TBOS</i> can achieve an improvement of 6.08% FAR (false alarm rate) for optimal-injection attacks, an improvement of 3.83% FAR in average for co-visitation injection attacks, as well as an improvement of 2.3% for profile injection attacks over benchmarks in terms of FAR while keeping the highest DR (detection rate). Additional experiments on real-world data show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TBOS</i> brings an improvement with the advantage of 6.5% FAR in average compared with baselines.

A Click Chemistry Approach to Targeted DNA Crosslinking with cis-Platinum(II)-Modified Triplex-Forming Oligonucleotides.

Limitations of clinical platinum(II) therapeutics include systemic toxicity and inherent resistance. Modern approaches, therefore, seek new ways to deliver active platinum(II) to discrete nucleic acid targets. In the field of antigene therapy, triplex‐forming oligonucleotides (TFOs) have attracted interest for their ability to specifically recognise extended duplex DNA targets. Here, we report a click chemistry based approach that combines alkyne‐modified TFOs with azide‐bearing cis‐platinum(II) complexes—based on cisplatin, oxaliplatin, and carboplatin motifs—to generate a library of PtII‐TFO hybrids. These constructs can be assembled modularly and enable directed platinum(II) crosslinking to purine nucleobases on the target sequence under the guidance of the TFO. By covalently incorporating modifications of thiazole orange—a known DNA‐intercalating fluorophore—into PtII‐TFOs constructs, enhanced target binding and discrimination between target and off‐target sequences was achieved.

A Click Chemistry Approach to Targeted DNA Crosslinking with cis‐Platinum(II)‐Modified Triplex‐Forming Oligonucleotides

AbstractLimitations of clinical platinum(II) therapeutics include systemic toxicity and inherent resistance. Modern approaches, therefore, seek new ways to deliver active platinum(II) to discrete nucleic acid targets. In the field of antigene therapy, triplex‐forming oligonucleotides (TFOs) have attracted interest for their ability to specifically recognise extended duplex DNA targets. Here, we report a click chemistry based approach that combines alkyne‐modified TFOs with azide‐bearing cis‐platinum(II) complexes—based on cisplatin, oxaliplatin, and carboplatin motifs—to generate a library of PtII‐TFO hybrids. These constructs can be assembled modularly and enable directed platinum(II) crosslinking to purine nucleobases on the target sequence under the guidance of the TFO. By covalently incorporating modifications of thiazole orange—a known DNA‐intercalating fluorophore—into PtII‐TFOs constructs, enhanced target binding and discrimination between target and off‐target sequences was achieved.

Time and phase synchronization using clutter observations in airborne distributed coherent aperture radars

Airborne Distributed Coherent Aperture Radar (ADCAR) is one of the most promising next-generation radars to significantly improve target detection and discrimination abilities. However, time and phase synchronization among unit radars should be done before an ADCAR is intended to cohere on a potential target. To address this problem, a time and phase synchronization technique using clutter observations is proposed in this paper. Clutter returns from different azimuths and elevations on the surface of the earth are employed to calibrate system uncertainties. Two stages are mainly considered: a scene registration among range-Doppler units from different transmit/receive pairs is performed to enhance the clutter coherence in the first stage, followed by a joint estimation of those synchronization errors in the second stage. To relieve the computational burden, a novel Separable and Sequential Estimation (SSE) method is provided to separate the unknowns at the sacrifice of a range-Doppler unit. Moreover, performance analyses including the clutter coherence ability, estimation lower bound, and signal coherence loss are also performed. Finally, simulation results indicate that ADCAR time and phase synchronization is realized by using our methods.

Nonlinear, neuronal adaptation in insect vision models improves target discrimination within repetitively moving backgrounds

Neurons which respond selectively to small moving targets, even against a cluttered background, have been identified in several insect species. To investigate what underlies these robust and highly selective responses, researchers have probed the neuronal circuitry in target-detecting, visual pathways. Observations in flies reveal nonlinear adaptation over time, composed of a fast onset and gradual decay. This adaptive processing is seen in both of the independent, parallel pathways encoding either luminance increments (ON channel) or decrements (OFF channel). The functional significance of this adaptive phenomenon has not been determined from physiological studies, though the asymmetrical time course suggests a role in suppressing responses to repetitive stimuli. We tested this possibility by comparing an implementation of fast adaptation against alternatives, using a model of insect ‘elementary small target motion detectors’. We conducted target-detecting simulations on various natural backgrounds, that were shifted via several movement profiles (and target velocities). Using performance metrics, we confirmed that the fast adaptation observed in neuronal systems enhances target detection against a repetitively moving background. Such background movement would be encountered via natural ego-motion as the insect travels through the world. These findings show that this form of nonlinear, fast-adaptation (suitably implementable via cellular biophysics) plays a role analogous to background subtraction techniques in conventional computer vision.

Effect of background clutter on neural discrimination in the bat auditory midbrain.

The discrimination of complex sounds is a fundamental function of the auditory system. This operation must be robust in the presence of noise and acoustic clutter. Echolocating bats are auditory specialists that discriminate sonar objects in acoustically complex environments. Bats produce brief signals, interrupted by periods of silence, rendering echo snapshots of sonar objects. Sonar object discrimination requires that bats process spatially and temporally overlapping echoes to make split-second decisions. The mechanisms that enable this discrimination are not well understood, particularly in complex environments. We explored the neural underpinnings of sonar object discrimination in the presence of acoustic scattering caused by physical clutter. We performed electrophysiological recordings in the inferior colliculus of awake big brown bats, to broadcasts of prerecorded echoes from physical objects. We acquired single unit responses to echoes and discovered a subpopulation of IC neurons that encode acoustic features that can be used to discriminate between sonar objects. We further investigated the effects of environmental clutter on this population's encoding of acoustic features. We discovered that the effect of background clutter on sonar object discrimination is highly variable and depends on object properties and target-clutter spatiotemporal separation. In many conditions, clutter impaired discrimination of sonar objects. However, in some instances clutter enhanced acoustic features of echo returns, enabling higher levels of discrimination. This finding suggests that environmental clutter may augment acoustic cues used for sonar target discrimination and provides further evidence in a growing body of literature that noise is not universally detrimental to sensory encoding.NEW & NOTEWORTHY Bats are powerful animal models for investigating the encoding of auditory objects under acoustically challenging conditions. Although past work has considered the effect of acoustic clutter on sonar target detection, less is known about target discrimination in clutter. Our work shows that the neural encoding of auditory objects was affected by clutter in a distance-dependent manner. These findings advance the knowledge on auditory object detection and discrimination and noise-dependent stimulus enhancement.

No effects of rhythmic visual stimulation on target discrimination: An online alpha entrainment experiment.

Previous research established that rhythmic sensory stimulation can affect subsequent stimulus perception, possibly through ‘entrainment’ of oscillations in the brain. Alpha frequency is a natural target for visual entrainment, because fluctuations in posterior alpha oscillations have been linked to visual target detection or discrimination. On the other hand, alpha oscillations also relate to attentional mechanisms, such as attentional orienting or selection. Previous visual alpha entrainment studies focused on differential processing of targets presented in‐phase with the preceding rhythmic stimulation relative to out‐of‐phase targets (an ‘SOA effect’), putatively related to the phase of entrained neuronal alpha oscillations. Fewer studies probed the consequences of rhythmic alpha stimulation for attention mechanisms related to alpha power. Here, we asked whether alpha stimulation of one hemifield has similar effects on reaction times as we see for increased alpha synchronization in magneto/electroencephalography (M/EEG) studies (i.e., more alpha means impaired processing and functional inhibition). We implemented a task inspired by attention studies, assessing reaction times to ipsilateral vs. contralateral visual targets, with and without concurrent presentation of distractors. Yet, in place of any attention cues, we presented a rhythmic, vs. arrhythmic, alpha‐frequency train of visual flashes to one hemifield, in a large sample size (N = 115) in an online experiment. We found clear evidence that flash train rhythmicity did not impact task performance. We also found that the spatial congruence between the unilateral flash train and the subsequent visual target did impact response times but only in the presence of contralateral distractor stimuli. We discuss implications, limitations and future directions.