Biology subjects

Purokayastha, S.

Publications and source records attributed to Purokayastha, S..

5 recordsLinked to original sources

bioRxiv2024

Do microsaccades vary with discriminability around the visual field?

Microsaccades-tiny fixational eye movements- improve discriminability in high acuity tasks in the foveola. To investigate whether they help compensate for low discriminability at perifovea, we examined MS characteristics relative to the adult visual performance field, which is characterized by two perceptual asymmetries: Horizontal-Vertical Anisotropy (better discrimination along the horizontal than vertical meridian), and Vertical Meridian Asymmetry (better discrimination along the lower-than upper-vertical meridian). We investigated whether and to what extent microsaccade directionality varies when stimuli are at isoeccentric locations along the cardinals under conditions of heterogeneous discriminability (Experiment 1) and homogeneous discriminability, equated by adjusting stimulus contrast (Experiment 2). Participants performed a two-alternative forced-choice orientation discrimination task. In both experiments, performance was better on trials without microsaccades between ready signal onset and stimulus offset than on trials with microsaccades. Across the trial sequence the microsaccade rate and directional pattern were similar across locations. Our results indicate that microsaccades were similar regardless of stimulus discriminability and target location, except during the response period-once the stimuli were no longer present and target location no longer uncertain-when microsaccades were biased toward the target location. Thus, this study reveals that microsaccades do not flexibly adapt as a function of varying discriminability in a basic visual task around the visual field.

neuroscience↗

bioRxiv2021

Stimulus-induced narrowband gamma oscillations are test-retest reliable in healthy elderly in human EEG

Visual stimulus-induced narrowband gamma oscillations in electroencephalogram (EEG) recordings have been recently shown to be compromised in subjects with Mild Cognitive Impairment or Alzheimers Disease (AD), suggesting that gamma could be an inexpensive and easily accessible biomarker for early diagnosis of AD. However, to use gamma as a biomarker, its characteristics should remain consistent across multiple recordings, even when separated over long intervals. Previous magnetoencephalography studies in young subjects have reported that gamma power remains consistent over recordings separated by a few weeks to months. Here, we assessed the consistency of slow (20-35 Hz) and fast gamma (36-66 Hz) oscillations induced by static full-field gratings in male (N=20) and female (N=20) elderly subjects (>49 years) in EEG recordings separated by more than a year, and tested the consistency in the magnitude of gamma power, its temporal evolution and spectral profile. Gamma oscillations had distinct spectral and temporal characteristics across subjects, which remained consistent across recordings (average intraclass correlation, ICC of [~]0.7). Alpha oscillations (8-12 Hz) and steady-state-visually-evoked-potentials (SSVEPs) were also found to be reliable. We further tested how EEG features can be used to identify two recordings as belonging to the same versus different subjects and found high classifier performance (area under ROC curve of [~]0.89), with the temporal evolution of slow gamma and spectral profile emerging as the most informative features. These results suggest that EEG gamma oscillations are reliable across recordings and can be used as a clinical biomarker as well as a potential tool for subject identification. Significance statementWe demonstrate the reliability of stimulus-induced gamma oscillations in elderly humans for the first time in EEG. Since gamma has recently been shown to be compromised in patients with Mild Cognitive Impairment or early Alzheimers Disease (AD), together these results mark the first steps towards an EEG based clinical biomarker for early diagnosis of AD. We observed high reliability in the power spectrum, gamma power and its temporal characteristics, within the test-retest period of one year. Alpha and steady-state-visually-evoked potential power were also found to be reliable. These spectral and temporal features could also be used to identify EEG recordings as belonging to the same versus different subjects with high performance, suggesting a potentially key role in subject identification also.

neuroscience↗

bioRxiv2019

Implicit perceptual memory can increase or decrease with ageing

A decline in declarative or explicit memory has been extensively characterized in cognitive ageing and is a hallmark of cognitive impairments. However, whether and how implicit perceptual memory varies with ageing or cognitive impairment is unclear. Here, we compared implicit perceptual memory and explicit memory measures in three groups of subjects: (1) 59 healthy young volunteers (20-30 years); (2) 238 healthy old volunteers (50-90 years) and (3) 21 patients with mild cognitive impairment MCI (50-90 years). To measure explicit memory, subjects were tested on standard recognition and recall tasks. To measure implicit perceptual memory, we used a classic perceptual priming paradigm. Subjects had to report the shape of a visual search pop-out target. Implicit priming was measured as the speedup in response time for targets with the same vs different color/position on consecutive trials.\n\nOur main findings are as follows: (1) Explicit memory was weaker in old compared to young subjects, and in MCI compared to age-matched controls; (2) Surprisingly, implicit perceptual memory did not always decline with age: color priming was smaller in older subjects but position priming was larger; (3) Position priming was less frequent in the MCI group compared to age-matched controls; (4) Implicit and explicit memory measures were uncorrelated in all three groups. Thus, implicit memory can increase or decrease with age or cognitive impairment, but this decline does not covary with explicit memory. We propose that incorporating explicit and implicit measures can yield a richer characterization of memory.

animal behavior and cognition↗

bioRxiv2019

Fast gamma oscillations weaken with age in healthy elderly in human EEG

Gamma rhythms ([~]20-70 Hz) have been reported to be abnormal in mental disorders such as autism and schizophrenia in humans, and Alzheimers disease (AD) models in rodents. However, the effect of normal aging on these oscillations is not known, especially for elderly subjects (>49 years) for which AD is most prevalent. In a first large-scale (236 subjects; 104 females) electroencephalogram (EEG) study on gamma oscillations on elderly subjects (aged 50-88 years), we presented full-screen Cartesian gratings that induced two distinct gamma oscillations (slow: 20-34 Hz and fast: 36-66 Hz). Power and centre frequency significantly decreased with age for both slow and fast gamma, but not alpha (8-12 Hz). Reduction was more salient for fast gamma than slow. These results were independent of microsaccades and pupillary reactivity to stimulus, as well as variations in power spectral density with age. Steady-state visual evoked potentials (SSVEPs) also reduced with age. These results are crucial first steps towards using gamma/SSVEPs as biomarkers of cognitive decline in elderly.\n\nSignificance statementNo study in humans has examined visual narrow-band gamma oscillations with healthy aging in elderly subjects. In a first large-scale (236 subjects) EEG study on stimulus-induced narrow band gamma in cognitively normal elderly (>49 years) humans, we show that both power and centre frequency of slow and fast gamma (20-34 Hz and 36-66 Hz respectively) decrease with age, but alpha power does not. Steady-state visual evoked potential (SSVEPs) in gamma range also decrease with age. Any EEG-based biomarker is accessible and affordable to patients of a wide socio-economic spectrum. Our results are important steps for developing such screening/diagnostic tests for aging-related diseases, like Alzheimers disease.

neuroscience↗

bioRxiv2019

Neurally-constrained modeling of human gaze strategies in a change blindness task

Visual attention enables us to engage selectively with the most important events in the world around us. Yet, sometimes, we fail to notice salient events. \"Change blindness\" - the surprising inability to detect and identify salient changes that occur in flashing visual images - enables measuring such failures in a laboratory setting. We discovered that human participants (n=39) varied widely (by two-fold) in their ability to detect changes when tested on a laboratory change blindness task. To understand the reasons for these differences in change detection abilities, we characterized eye-movement patterns and gaze strategies as participants scanned these images. Surprisingly, we found no systematic differences between scan paths, fixation maps or saccade patterns between participants who were successful at detecting changes, versus those who were not. Yet, two low-level gaze metrics - the mean fixation duration and the variance of saccade amplitudes - systematically predicted change detection success. To explain the mechanism by which these gaze metrics could influence performance, we developed a neurally constrained model, based on the Bayesian framework of sequential probability ratio testing (SPRT), which simulated gaze strategies of successful and unsuccessful observers. The models ability to detect changes varied systematically with mean fixation duration and saccade amplitude variance, closely mimicking observations in the human data. Moreover, the models success rates correlated robustly with human observers success rates, across images. Our model explains putative human attention mechanisms during change blindness tasks and provides key insights into effective strategies for shifting gaze and attention for artificial agents navigating dynamic, crowded environments.\n\nAuthor SummaryOur brain has the remarkable capacity to pay attention, selectively, to the most important events in the world around us. Yet, sometimes, we fail spectacularly to notice even the most salient events. We tested this phenomenon in the laboratory with a change-blindness experiment, by having participants freely scan and detect changes across discontinuous image pairs. Participants varied widely in their ability to detect these changes. Surprisingly, their success correlated with differences in low-level gaze metrics. A Bayesian model of eye movements, which incorporated neural constraints on stimulus encoding, could explain the reason for these differences, and closely mimicked human performance in this change blindness task. The models gaze strategies provide relevant insights for artificial, neuromorphic agents navigating dynamic, crowded environments.

neuroscience↗