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1.
bioRxiv ; 2024 Apr 25.
Article in English | MEDLINE | ID: mdl-38496414

ABSTRACT

We used two-photon imaging to record from granular and supragranular layers in mouse primary visual cortex (V1) under spontaneous conditions and applied an extension of the spike time tiling coefficient (STTC; introduced by Cutts and Eglen) to map functional connectivity architecture within and across layers. We made several observations: Approximately, 19-34% of neuronal pairs within 300 µm of each other exhibit statistically significant functional connections, compared to ~10% at distances of 1mm or more. As expected, neuronal pairs with similar tuning functions exhibit a significant, though relatively small, increase in the fraction of functional inter-neuronal correlations. In contrast, internal state as reflected by pupillary diameter or aggregate neuronal activity appears to play a much stronger role in determining inter-neuronal correlation distributions and topography. Overall, inter-neuronal correlations appear to be slightly more prominent in L4. The first-order functionally connected (i.e., direct) neighbors of neurons determine the hub structure of the V1 microcircuit. L4 exhibits a nearly flat degree of connectivity distribution, extending to higher values than seen in supragranular layers, whose distribution drops exponentially. In all layers, functional connectivity exhibits small-world characteristics and network robustness. The probability of firing of L2/3 pyramidal neurons can be predicted as a function of the aggregate activity in their first-order functionally connected partners within L4, which represent their putative input group. The functional form of this prediction conforms well to a ReLU function, reaching up to firing probability one in some neurons. Interestingly, the properties of L2/3 pyramidal neurons differ based on the size of their L4 functional connectivity group. Specifically, L2/3 neurons with small layer-4 degrees of connectivity appear to be more sensitive to the firing of their L4 functional connectivity partners, suggesting they may be more effective at transmitting synchronous activity downstream from L4. They also appear to fire largely independently from each other, compared to neurons with high layer-4 degrees of connectivity, and are less modulated by changes in pupil size and aggregate population dynamics. Information transmission is best viewed as occurring from neuronal ensembles in L4 to neuronal ensembles in L2/3. Under spontaneous conditions, we were able to identify such candidate neuronal ensembles, which exhibit high sensitivity, precision, and specificity for L4 to L2/3 information transmission. In sum, functional connectivity analysis under spontaneous activity conditions reveals a modular neuronal ensemble architecture within and across granular and supragranular layers of mouse primary visual cortex. Furthermore, modules with different degrees of connectivity appear to obey different rules of engagement and communication across the V1 columnar circuit.

2.
J Eye Mov Res ; 14(2)2021.
Article in English | MEDLINE | ID: mdl-34745441

ABSTRACT

The main purpose of this study is to compare the silent and loud reading ability of typical and dyslexic readers, using eye-tracking technology to monitor the reading process. The participants (156 students of normal intelligence) were first divided into three groups based on their school grade, and each subgroup was then further separated into typical readers and students diagnosed with dyslexia. The students read the same text twice, one time silently and one time out loud. Various eye-tracking parameters were calculated for both types of reading. In general, the performance of the typical students was better for both modes of reading - regardless of age. In the older age groups, typical readers performed better at silent reading. The dyslexic readers in all age groups performed better at reading out loud. However, this was less prominent in secondary and upper secondary dyslexics, reflecting a slow shift towards silent reading mode as they age. Our results confirm that the eye-tracking parameters of dyslexics improve with age in both silent and loud reading, and their reading preference shifts slowly towards silent reading. Typical readers, before 4th grade do not show a clear reading mode preference, however, after that age they develop a clear preference for silent reading.

3.
PLoS One ; 12(8): e0182597, 2017.
Article in English | MEDLINE | ID: mdl-28800632

ABSTRACT

Dyslexia is a developmental learning disorder of single word reading accuracy and/or fluency, with compelling research directed towards understanding the contributions of the visual system. While dyslexia is not an oculomotor disease, readers with dyslexia have shown different eye movements than typically developing students during text reading. Readers with dyslexia exhibit longer and more frequent fixations, shorter saccade lengths, more backward refixations than typical readers. Furthermore, readers with dyslexia are known to have difficulty in reading long words, lower skipping rate of short words, and high gaze duration on many words. It is an open question whether it is possible to harness these distinctive oculomotor scanning patterns observed during reading in order to develop a screening tool that can reliably identify struggling readers, who may be candidates for dyslexia. Here, we introduce a novel, fast, objective, non-invasive method, named Rapid Assessment of Difficulties and Abnormalities in Reading (RADAR) that screens for features associated with the aberrant visual scanning of reading text seen in dyslexia. Eye tracking parameter measurements that are stable under retest and have high discriminative power, as indicated by their ROC (receiver operating characteristic) curves, were obtained during silent text reading. These parameters were combined to derive a total reading score (TRS) that can reliably separate readers with dyslexia from typical readers. We tested TRS in a group of school-age children ranging from 8.5 to 12.5 years of age. TRS achieved 94.2% correct classification of children tested. Specifically, 35 out of 37 control (specificity 94.6%) and 30 out of 32 readers with dyslexia (sensitivity 93.8%) were classified correctly using RADAR, under a circular validation condition (see section Results/Total Reading Score) where the individual evaluated was not included in the test construction group. In conclusion, RADAR is a novel, automated, fast and reliable way to identify children at high risk of dyslexia that is amenable to large-scale screening. Moreover, analysis of eye movement parameters obtained with RADAR during reading will likely be useful for implementing individualized treatment strategies and for monitoring objectively the success of chosen interventions. We envision that it will be possible to use RADAR as a sensitive, objective, and quantitative first pass screen to identify individuals with reading disorders that manifest with abnormal oculomotor reading strategies, like dyslexia.


Subject(s)
Dyslexia/diagnosis , Eye Movements , Pattern Recognition, Automated/methods , Reading , Adolescent , Case-Control Studies , Child , Comprehension/physiology , Dyslexia/physiopathology , Female , Humans , Learning/physiology , Male , ROC Curve , Research Design
4.
Neural Comput ; 25(9): 2265-302, 2013 Sep.
Article in English | MEDLINE | ID: mdl-23663145

ABSTRACT

In this work, the Shannon information transfer rate due to the transmission of a linear combination of the firing rates of a number of afferent neurons is examined. The transmission of this linear combination (transfer statistic) takes place through a stochastic firing process, while a rate code is assumed. Constraints are imposed on the transmission process by the requirement that the coefficient of variation for the transfer statistic is small and by the relative variance of the individual terms in the calculation of the statistic. In the regime of no noise or signal correlations among the input neurons, simulations suggest that information transfer for fixed overall input is favored when there are few high-firing neurons, as opposed to more lower-firing neurons. Signal correlations among low-firing neurons can result in aggregates of high firing rates, improving in this way information transfer and calculational robustness. Under reasonable rate code assumptions, information transfer rates obtained are of the order 3 to 10 bit/sec.


Subject(s)
Models, Neurological , Neurons, Afferent/physiology , Action Potentials/physiology , Animals , Computer Simulation , Humans , Linear Models , Synaptic Transmission/physiology
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