Temporal Processing of Sensory Inputs and Time ...

Temporal Processing of Sensory Inputs and Time Measurement by Brain

The measurement of time by our mind appears to be a very complex process, which is linked to our sense of passage or flow of time. Based on the successful survival of various members of animal kingdom in a complex world around us, which is a four dimensional physical universe after combining ‘time’, it would be a reasonable inference that other animals also have a sense of flow of time, and are able to measure time with a varying degree of accuracy. This view is consistent with the input of “Newtonian time” by predators such as tigers in calculating the trajectories for catching prey.

A recent study in monkeys has shown that activity of neurons in lateral parietal area (LIP) decreases at a constant rate between abrupt timed motor activities of eye, called saccades (5). This is interesting in view of an earlier study in monkeys showing that neurons with monotonically decreasing or increasing activities in motor and pre-motor cortex, were predictors of temporal intervals before the movements (3). Study by Schneider, et al (5) showed that intervals between saccades were kept very precise following the initial training with juice rewards. The onset of eye movement or saccade was predictable by the magnitude of threshold frequency reached by neurons in LIP, whose activity progressively decreased after being reset immediately after the saccade. They also confirmed that LIP neurons selectively responded to spatial differences, namely peripheral versus central targets, consistent their previously known characteristics. Notably, they found that that there was no significant difference between adjacent inter-saccade time intervals, emphasizing the ‘mechanism’ to maintain accuracy is probably originating from higher centers as they have noted. In another study, Lebedev et al (3) had shown that intention to produce movement is predicted by increasing or decreasing activity of groups of neurons in motor and premotor cortex. Both studies are consistent with the view that motor activities are employed in brain as a clock for measuring time. The study by Schneider et al has further shown that measurements of time within short periods of period are very accurate. But the role of this mechanism in measuring time intervals such as 5, 10, 60 minutes by humans, which are not very accurate, may not be clear without further studies. It is likely that we measure time by a similar mechanism, involving circuits producing the ‘motor outputs’, which leads to the following hypothesis: The circuits similar to that producing “saccades” may be measuring time, but without resulting in ‘actual motor’ activities. Role of evolution in formation of circuits responsible for measurement of time and sensory processing in primates: At least parts of premotor/prefrontal area may have evolved from the duplication of sophisticated motor cortex circuits and may be responsible for (a) measurement of time (b) generating intention of producing motor activity (c) processing of the sensory information. The above findings (3, 5) may be an evidence of duplication of motor cortex in primates. A subpopulation of circuits in premotor/prefrontal cortex may be generating a series of motor commands, not resulting in any actual motor acts, such as saccades, but are associated with mechanisms associated with measurement of time. The recording of decreasing or increasing activity may be common events, throughout the cortex, associated with circuits playing role in measurement of time. Thus the long pyramidal neurons originating from premotor/prefrontal cortex may be responsible for the decreasing activity of neurons during timed saccades in LIP as reported recently (5). In addition, it is likely that pyramidal neurons from

Temporal Processing of Sensory Inputs and Time Measurement by Brain

premotor/prefrontal cortex are projecting to the sensory association cortex, where they are part of the mechanism underlying the temporal processing of sensory information. The above theory is not exclusive of my proposed hypothesis of sensory time units called ‘sensory moment’ which is defined as the time interval between two adjacent frames of integrated sensory outputs. It appears more appealing to me that the frequency of generation of ‘frames of sensory output’ will determine “our perception of flow of time”. My hypothesis of temporal processing of sensory information is expanded to reconcile above findings in the following paragraphs. Role of neurons with decreasing and increasing outputs in temporal processing of sensory information and measurement of time: The hypothesis of the temporal processing of sensory inputs (information) predicts the existence of a subpopulation of neurons, named here ‘Sensory Integrator (SI) Neurons’ that are excited by inputs coming from different sensory areas of brain, which includes primary somatosensory cortex, auditory cortex, visual cortex as well as other parts of the central nervous system, such as cerebellum. The SI neurons are inhibited by neurons, such as those reported recently by Schneider, et al (5). The neurons reported by Schneider, et al (5) show decreasing activity. If the neurons showing tonically decreasing activity are inhibitory (to be called frequency modulator neurons or FM neurons), then inhibitory activity will reach a low threshold, when it would allow the SI neuron to be sufficiently un-inhibited to cause its firing, leading to integration of sensory inputs. A reasonable separation of sensory outputs provided by this mechanism will be necessary for the temporal processing of sensory inputs. On the other hand, if the neuron is excitatory, then its increasing activity will allow the SI neuron to reach a threshold, so that it can fire, resulting in an integrated sensory output. I further believe that decreasing activity of inhibitory neurons is more likely to play role in determining the time interval between sensory outputs, influencing our sense of time (see the schematic). The decreasing activity of FM neurons may be the result of auto-inhibition from its own inhibitory output. In addition, the conclusion of Schneider, et al (5) that sensory events ‘reset’ the clock, which is probably a result of the returning excitatory outputs from the ‘Integrator Neuron’, acting on the FM neurons. The FM neurons activity is inhibited by its own inhibitory output, but inputs arriving from the SI neuron will reactivate (called ‘reset’ of FM neurons) the neurons so that it will begin a new phase of activity. Hence inputs from motor circuits controlling saccades are responsible for setting the activity phase of FM neurons (shown in the schematic on next page), which is learned by monkeys as a result of training, and it helps monkeys keep time as reported recently (5). Role of FM neurons in temporal processing of sensory information: The FM neurons with decreasing inhibitory outputs have a critical and an important role in the temporal processing of sensory information by SI neurons. The SI neuron will generate an integrated output of the sensory inputs, ONLY when the firing of inhibitory FM neuron reaches a low frequency such that inhibition of SI neuron is reduced to a low level. Thus, because of the role of FM neurons in timing the outputs from SI neurons, the integrated sensory output represents all sensory inputs generated at a single point in time. This role of FM neurons is extremely helpful in reducing noise levels in our sensory perception. The FM neuron can vary its frequency of ‘periods of decreasing firing rate’ so that it matches the frequencies of various

Temporal Processing of Sensory Inputs and Time Measurement by Brain

inputs, such as auditory, visual, somatosensory (deep touch, light touch, vibrotactile stimuli, etc.). The period of decreasing firing rate (PDFR) of inhibitory FM neuron is defined as “the period after reset of FM neuron when its firing rate is maximum till the time when the activity of FM neuron reaches its lowest level immediately before being reset again”. The SI neuron will fire at the end of PDFR, when the inhibitory effect of FM neuron reaches a low level. At the end of PDFR, an excitatory output from SI neuron will quickly reset the FM neuron, when FM neuron will once again begin generating the inhibitory outputs to inhibit the integrator neuron. Thus, a single PDFR interval of FM neuron will equal in length as that of a single ‘sensory moment’. Since FM neurons are inhibitory, they are likely to be cortical GABAergic interneurons. The increased release of inhibitory neurotransmitter GABA would result in a faster pace of decrement in the activities of FM neurons leading to shorter PDFR intervals. The inhibitory FM neuron is likely to form synapses at the initial axon region of the integrator neuron, which will give FM neurons greater control over the activity of integrator neurons (see the schematic). Role of combined spatial and temporal inhibition of SI Neuron by FM neurons: The change in the frequency of neurons in self timed saccade task in the study by Schneider, et al (2012)(5) represents a change of about 30%. A decrease of about 30% in the frequency of rate of firing by inhibitory FM neurons alone may not be sufficient to explain un-inhibition of a neuron. The effect of inhibitory neuron on the Integrator neuron may be both (1) temporally via changes in frequency, and (2) spatially summated. Combined inhibitory effect on Integrator neurons of spatial and temporal summation may be an exponential function of frequency of FM neurons. The effect of temporal summation is due to a reduction in the frequency of firing of FM neurons. The spatial summation on the other hand may be due to arborization of the nerve endings of FM neurons, resulting in several spatially distinct inhibitory inputs of the same FM neuron on a single SI neuron. The exponential decline of inhibition of the SI neuron at a critically low frequency of FM neuron may be an important factor determining the reproducibility of PDFR intervals. Other factors influencing the length of PDFR intervals may be the role of Na+/K+ pumps, which restores ionic concentrations of axoplasm following an action potential. Role of PDFR of inhibitory FM neurons in the “mechanism of attention”: The frequency of PDFRs of the FM neuron may alter in order to synchronize with the frequency of a particular sensory input, for example, auditory, visual, tactile or noxious stimuli, arriving at the SI (sensory integrator) neurons, which would allow us to focus on a particular sensory stimulus at a given time. Accordingly, we are able to shift our attention from one type of stimulus, for example, from visual to auditory stimulus by changing the frequency of PDFRs of FM neurons. That is why when we listen attentively to a person, we ‘gaze’ on that person or a particular point in space, which could be due to a greater match of the PDFR interval frequency with frequency of auditory inputs than visual inputs during a state of attentive listening. Furthermore, the states of visual or auditory hallucination may result from a mismatch between the frequencies of PDFR and visual/auditory inputs. One of proposed experiments to test this hypothesis would be to use recording methods from Nicolelis laboratory to see if the PDFRs of neurons with

Temporal Processing of Sensory Inputs and Time Measurement by Brain

monotonically decreasing or increasing activity in primate cortex are affected by shifting attention to different sensory stimuli.

Role of thalamus in synchronizing different sensory inputs: There are lagged cells, shown in cats and monkeys in lateral geniculate nucleus (LGN) of thalamus, which exhibit phase delay with respect nonlagged cells of LGN in response to flashing stimuli (4). The less responsive lagged cells (4) may be responsible for providing inputs to SI neurons because they can undergo phase shifts, likely less than a cycle long, adjusting to other inputs, such as auditory, somatosensory inputs needed to produce meaningful sensory outputs. Mechanisms, such as differences in the kinetics of open states of different ion channels discussed earlier (4), may play role in mechanisms producing phase shifts. The same mechanisms could also assist in the synchronization of various types of sensory signals reaching SI neurons in the association cortex. In addition the phase shift may be also caused by flow of sensory inputs via polysynaptic pathways prior to converging on to SI neurons, wherein each synaptic delay will shift a phase in order to synchronize different sensory inputs. Measurement of time by Brain: According to my hypothesis, brain uses a unit of time called ‘sensory moments’ to measure time, which is defined as the interval between two consecutive outputs from SI (sensory integrator) neuron receiving sensory inputs from different sources, such as somatosensory, visual and auditory cortex. Also, as discussed above, the period of decreasing firing rate or PDFR of FM neurons would determine the interval between two sensory outputs or the length of ‘sensory moment’ measured in actual time. If the ‘sensory moment’ is reduced by half vis a vis actual time due to decreased actual intervals of PDFRs, then, as shown in the schematic, the subject would report that the ‘actual one hour’ felt like ‘two hours’. The decrease of intervals of PDFR would result from increased auto-inhibition of FM neurons, which could follow increased release of inhibitory neurotransmitters, such as GABA. Thus, according to my hypothesis, drugs increasing GABAergic activity in brain could result in reporting of ‘slowing of time’ by subjects. It has been shown that activation of HT2A/C receptors increases GABA levels and activity of GABAergic interneurons in rat prefrontal cortex (1), which is discussed below to support my hypothesis. Effect of hallucinogen on mental measurement of time: In a study, participants who were given hallucinogen psilocybin experienced the elapsed time to have been greater than it actually was (7). Increased auto-inhibition of FM neurons may lead to shorter PDFR intervals, which will reduce the time intervals between two consecutive outputs from integrator neuron, called ‘sensory moments’, resulting in subjective reporting of ‘slowing of time’ by the subjects. Since psilocybin is shown to produce schizophrenia like psychosis via activation 5HT2A/1A receptors (6), the increased GABAergic activity of FM may be mediated by 5HT2A receptors, reducing PDFR intervals via enhanced auto-inhibition. Decreased time intervals separating two consecutive outputs resulting from sensory inputs arriving at an SI (see the schematic), would also produce an increase in the ‘noise’ level, accounting for the psychotic and hallucinogenic effects of psilocybin. Classification of FM neurons: Based on evidence from recent studies, as discussed above, presence of two types of FM neurons, inhibitory and excitatory, is indicated with decreasing and increasing activities,

Temporal Processing of Sensory Inputs and Time Measurement by Brain

respectively. The greater temporal accuracy of motor tasks, such as a tiger catching its prey indicates the role of neuron from motor, premotor or prefrontal cortex in “kickstarting” a subcategory of FM neurons. Thus, it is hypothesized that there are at least two types of inhibitory (PDFR) FM neurons: Type I FM Neuron: These FM neurons are constitutively active in an awake state. Type II FM neuron: These FM neuron become active only during motor tasks, and may be associated with brain circuits involved in ‘intention to initiate a motor task’. The type I FM neurons may be constitutively active in awake states as a result of inputs from the reticular activating system and suprachiasmatic nucleus (circadian clock), which may contribute to our sense of the length of time based on diurnal rhythm. The processing of sensory inputs by SI neurons may be influenced by both types of FM neurons simultaneously, or at different times, which will depend upon the task involved. For example, increased motor nature of the task may result in a greater involvement of the type II FM neurons. Type I FM neurons may represent more modern neurons in evolutionary time scale. Evidence for presence of separate ‘frames of sensory outputs’: There is no clear cut experimental evidence supporting temporal processing of frames of sensory information. However, the observed peri-saccadic suppression of retinal images (2) can be explained by inhibition of output in dorsal stream resulting from retinal images by the FM neurons. Role of FM neurons in cognitive functions: As noted above, the PDFR interval of FM neurons is determined by a reset signal from SI neurons. There may be subpopulations of FM neurons with different PDFR interval frequencies involved in synchronization of special types of SI neurons processing only limited number or single, but not all sensory modalities, such as directions or colors. The processing of one single sensory modality such as direction or color code may be of critical importance in cognitive decision making processes. This proposed role of a group of FM neurons and associated SI neurons is consistent with dynamic synchronization between subnetworks in prefrontal cortex during behavioral performance reported in a poster presented at SFN (2012) meeting by Tim Buschman from Princeton Neuroscience Institute (Princeton, NJ) (http://www.timbuschman.com/node/37). The control of different SI neurons responding to only single or limited sensory inputs associated with a particular task by the same FM neuron may account for the observed synchronization of subnetworks in prefrontal cortex. The Importance of Study of FM neurons: A substantial process of our thought process is the intention to “do” something, a potential motor event. Hence, in view of above discussion, it would be natural to ask the following question: Are subpopulations of FM neurons the mouthpieces or ‘experimentally detected/detectable’ neurons receiving information from higher brain circuits that are involved in the conscious thought of doing something or ‘our intention’? The studies by Nicolelis lab have already shown that to be true (3). We all think in the language we are used speak. It is very likely that there are FM neurons providing inhibitory inputs for motor neurons in the speech area, which reduce their activity in order to cause the contraction of speech muscles. It is quite likely that outputs from the same FM neurons feed into other areas in brain, such as Wernicke area, a part of the temporal lobe, contributing to thought development in form of language. A thought process is likely to be correlated with the

Temporal Processing of Sensory Inputs and Time Measurement by Brain

overall activity of hundreds or more FM neurons in different phases of reaching their “threshold frequencies”.

The FM neurons are ‘detectable’ electrophysiological signature of our ‘intentions’ and ‘mental flow of time’ (3, 5), and they could play a central role in the temporal processing of sensory information. In conclusion, I believe that the study of FM neurons is important for the understanding of thought, consciousness and other cortical functions. Bibliography: 1. Abi-Saab WM, Bubser M, Roth RH, and Deutch AY. 5-HT2 receptor regulation of extracellular GABA levels in the prefrontal cortex. Neuropsychopharmacology 20: 92-96, 1999. 2. Bremmer F, Kubischik M, Hoffmann KP, and Krekelberg B. Neural dynamics of saccadic suppression. J Neurosci 29: 12374-12383, 2009. 3. Lebedev MA, O'Doherty JE, and Nicolelis MA. Decoding of temporal intervals from cortical ensemble activity. J Neurophysiol 99: 166-186, 2008. 4. Saul AB. Lagged cells in alert monkey lateral geniculate nucleus. Vis Neurosci 25: 647-659, 2008. 5. Schneider BA, and Ghose GM. Temporal production signals in parietal cortex. PLoS Biol 10: e1001413, 2012. 6. Vollenweider FX, Vollenweider-Scherpenhuyzen MF, Babler A, Vogel H, and Hell D. Psilocybin induces schizophrenia-like psychosis in humans via a serotonin-2 agonist action. Neuroreport 9: 38973902, 1998. 7. Wackermann J, Wittmann M, Hasler F, and Vollenweider FX. Effects of varied doses of psilocybin on time interval reproduction in human subjects. Neurosci Lett 435: 51-55, 2008.

‘Sensory moment’ is the unit of time for sensory clock, which is defined as the ‘interval’ between two consecutive ‘integrated outputs’ resulting from various sensory inputs, namely, visual (V), auditory (A), somatosensory (S), etc going to Sensory Integrator (SI) Neuron. A single sensory moment will equal a single period of decreasing firing rate (PDFR) of inhibitory FM neuron

Increase in frequency of outputs from SI neurons ( from 1/sec, below to 2/sec, right) causes perceived slowing of time: Actual one hour appears like two hours

S Neurons from prefrontal, motor, pre-motor cortex

Motor/ Sensory Integrator (SI) Neuron

V

A

Inhibitory Neuron (FM) with decreasing activity (PDFR) Schneider et al, 2012

RESET 1 sec RESET

Single sensory moment

Outputs may feed into ‘Time cells’ , reported by Howard Eichenbaum in Neuron Vol 71(4), 2011

1 sec

Output for temporal processing of sensory information in other cortical association areas