Neuron Jiayi Zhang/Liang Chen/Ying Mao of Fudan University reveals a new neural mechanism encoding time prediction information

iNature

Time is important in our daily lives, but our understanding of how the human brain regulates second-level time perception is limited
.

On October 3, 2022, Jiayi Zhang, Liang Chen and Ying Mao of Fudan University published a research paper entitled "Visual cortex encodes timing information in humans and mice" online at Neuron (IF=19), which showed that the visual cortex of humans and mice can encode temporal information
。 The study combined intracranial electrocerebral (SEEG) recordings from epilepsy patients and circuit anatomical displays in mice that the visual cortex (VC) encodes temporal information
.
The study first asked human participants to perform an interval timing task and found that VCs are a key timekeeping brain region
.
Optogenetic experiments were conducted in mice and VCs were found to play an important role
in interval time behavior.
The study further found that VC neurons fire in a time-preserving order and exhibit increased excitability
in a time-increasing manner.
Finally, the study demonstrates a self-correcting learning process
that generates interval time activities with scalar timing with a computational model.
The work reveals how local oscillations occurring in VCs that occur in the range of seconds to ten seconds correlate temporal information from the outside world to guide behavior
.
Most human behavior involves the perception
of space and time.
The human brain organizes sensory projections, including auditory, visual, and location maps, to perceive the space of the outside world
.
The perception of 24-hour order of time, known as circadian rhythms, is primarily driven by the suprachiasmatic nucleus of the
hypothalamus.
The perception and prediction of time patterns in the order of seconds to ten seconds is a prerequisite for
estimating the movement, dance, and musical performance of predators approaching animals as well as humans.
However, little
is known about timing representations in the human brain in the range of seconds to ten.
Much of what we know about the structure of the human brain in relation to time comes from studies
using functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), and magnetoencephalography (MEG).
These studies reveal different timekeeping-related brain networks in timed tasks, with speeds ranging from seconds to ten seconds
.
For example, basal ganglia, thalamus, insula, and cingulate parietal cortical networks are often associated
with interval tasks.
Phase analysis showed that θ and α-band oscillations in the visual and auditory cortex play an important role
in time-learning tasks.
This association was further confirmed
by transcranial stimulation studies and local perturbations of human V1.
These studies provide important evidence
for identifying time-related brain regions.
However, functional magnetic resonance imaging studies rely on indirect measurements of neural activity with limited
temporal resolution.
Although non-invasive EEG signals have a time resolution in milliseconds, the signal quality decreases
when penetrating the scalp and skull.
To address the question of which brain regions play a key role in human time perception in the order of seconds to ten seconds, the authors used stereoplephalogram (SEEG) recordings of 11 epilepsy patients to localize
seizures.
SEEG allows the measurement of intracranial electrical activity
at millisecond temporal resolution in awake humans performing interval timing tasks.
These recordings were recorded within 1 week of participants performing interval timing tasks each day
.
By performing power and phase analysis on 28 recorded brain regions, the authors propose that the visual cortex (VC) is a key brain region
for interval time behavior.
To further address the cellular and circuit mechanisms that mediate this timing behavior, the authors utilized circuit dissection tools
in mice.
Similar to humans, mice can also recognize and learn time series or visual cue reward timing
under visual stimulation.
Similar to the human temporal prediction paradigm, the authors performed simultaneous continuation behavior experiments
in mice.
To explore the expression of temporal information in the first generation of VCs (V1), the authors performed in vivo cell attachment and population recording on V1, revealing the plasticity changes and time-holding properties
of V1 neurons.
Computational modeling further illustrates the mechanism by which time information is represented in V1 circuits
.
The study shows that the primary VC acts as a local center that represents the temporal information
of the visual cue through intrinsic loop dynamics.
Zhang Jiayi, Chen Liang and Mao Ying are the co-corresponding authors of the paper; Yu Qingpeng, Bi Zedong, Jiang Shize, Yan Biao, Chen Heming, and Wang Yiting were the co-first authors of the paper, and a number of graduate students and technicians participated in the study
.

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