**Subject: Neural Dynamics**

**Hot times for the dorsal striatum**

David Robbe<fnref n="1" /> and Mostafa Safaie<fnref n="2" />

**Mini Abstract**

Using temperature manipulation, Monteiro and colleagues found a way to bidirectionally alter the speed of neuronal dynamics in the dorsal striatum of anesthetized rats. The same temperature manipulation selectively slowed down or sped up time perception, providing novel insights on the mechanisms of time-based decisions.

**Main Text**

Time is at the heart of most of our daily decisions and actions. As we stand at a pedestrian crossing, we often must make quick estimates as to whether we have enough time to make it across before an oncoming vehicle approaches. Well-timed behaviors are obviously not exclusive to humans; many other animals, as they forage, appear to wait or exploit food resources for precise durations or at regular time intervals. From such examples, it seems reasonable to assume that animals have an inner sense of time to make decisions based on duration. Still, the quest for the neuronal underpinning of time estimation, especially in the range of a few seconds, has been a wild one! At first, researchers assumed that animals tracked duration using internal clocks<fnref n="1" />, potentially centered around the dorsal striatum and its dopaminergic modulation<fnref n="2" />. More recently, the realization that time is inherently encoded in the dynamics of neuronal activity led to the proposal that duration could be *intrinsically* represented by neuronal ensembles distributed over multiple brain areas activated in a given timing task³. A difficulty with such a framework is to establish a causal relation between the evolving activity of a neuronal population and decisions based on duration. It is that precise challenge that Monteiro et al. have tackled in their recent study⁴, building on two important lines of work. On the one hand, population activity in the striatum has been previously shown to predict time-based binary decisions in rats⁵. On the other hand, manipulating the temperature of brain tissues has been previously shown to alter not only the speed of specific behavioral patterns⁶ but also the dynamics of neural circuit activity while preserving its overall structure⁷. Thus, to investigate the neural bases underlying time judgment, the authors asked two audacious questions. First, could striatal population dynamics be finely tuned by temperature? And second, would temperature manipulation of striatal tissue in behaving animals affect duration-based decisions?

To address these questions, Monteiro and colleagues developed a custom-built probe, based on the Peltier effect, to bidirectionally and quickly manipulate the temperature of the brain. They first used this probe to warm up (+1.5°) and cool down (two levels: -2.7° and -5.1°) the tissue and examined the impact of such manipulation on striatal neural activity evoked by stimulation of a sensory region of the thalamus. These experiments were performed under anesthesia to minimize neural modulations due to ongoing behavior. Importantly, the evoked response of striatal neurons lasted hundreds of milliseconds, most likely reflecting population dynamics across loops formed by the basal ganglia with thalamus and cortex. Using dimensionality reduction methods to represent striatal population dynamics as a trajectory in a 3D state space, the authors showed that cooling the striatum slowed down the evoked "trajectory" whereas warming accelerated it. Critically, this monotonic modulation of the population dynamics was observed despite an overall reduction in striatal firing rates during both warming and cooling regimes.

Next, the authors examined whether striatal population dynamics could provide information about time-based decisions. They used a categorization task (Figure 1A) in which rats heard two brief tones separated by an interval between 0.6 and 2.4 s. Upon presentation of the second tone and after estimating whether the interval was shorter or longer than an arbitrary reference set at 1.5 s, animals expressed their judgment by poking toward the left (long) or right (short) port. Rats were very good at discriminating between very short and long intervals, but their accuracy decreased for the two intervals nearest to the reference duration. The authors focused on those trials and replicated their previous observation that, during short trials misjudged as long, the striatal population dynamics had evolved more quickly⁵.

They then move to the more exciting part of their study: testing whether temperature manipulation could bias the interval duration judgment of near-boundary intervals. As predicted from the above electrophysiological experiments in behaving and anesthetized animals, warming the striatum led to a bias towards longer temporal

<footnote n="1">¹ Aix Marseille Université, Institut de Neurobiologie de la Méditerranée (INMED), INSERM, Turing Center for Living System, Marseille, France
david.robbe@inserm.fr</footnote>

<footnote n="2">² Department of Bioengineering, Imperial College London, London, UK</footnote>
judgments, while cooling the striatum had the opposite effect (Figure 1B-D). Although only one level of warming was performed due to technical limitations, larger manipulations during cooling trials resulted in larger decision biases. Critically, the monotonic influence of temperature was specific to the dorsal striatum, as manipulating the temperature of the overlying motor cortex failed to produce a similar effect.

Considering the vast body of evidence indicating the involvement of the dorsal striatum in controlling movement and decision speed⁸, the authors finally examined whether temperature manipulation affected the kinematics of the movements toward the reward ports, and reported that both cooling and warming the striatum led to slower movements and prolonged reaction times. Because temperature manipulation had non-monotonic effect on the firing rates of striatal neurons under anesthesia, Monteiro et al. concluded that the speed of population dynamics in the dorsal striatum regulates the judgment of time, while the average activity of its single neurons may provide a low-dimensional gain-like signal controlling the vigor of actions.

Altogether, the authors proposed the view that the speed of population dynamics in the dorsal striatum guides the when and what of action selection but does not control movement kinematics on a moment-to-moment basis. Such a conclusion is both exciting and provocative. It is stimulating because it may provide a way to bridge systems neuroscience in rodents with clinical observation in humans. Indeed, it is well known that patients with Parkinson's disease, which results in a malfunctional dorsal striatum, are capable, in specific contexts, of producing perfectly skilled actions, a phenomenon referred to as kinesia paradoxa⁹. This would make sense if the striatum controlled latent decisional processes rather than movements themselves. It is also provocative as there has been recent experimental evidence supporting the view that the sensorimotor region of the striatum continuously controls the kinematics of skilled movements¹⁰. In addition, electrophysiological recordings across the cortex and basal ganglia in non-human primates suggested that the basal ganglia influence the speed of deliberation but not what action to select (i.e., the when but not the what of action selection¹¹.

At this stage, we can only speculate about how to reconcile the distinct views on the striatal contribution to motor control and decision-making derived from the present and aforementioned studies. The devil, as often, might be in the details. Even though the authors provided evidence that gross movements did not directly influence time-based decisions, estimating time independently of movements remains largely an assumption as it is well known that animals, when forced to wait for specific durations, tend to produce stereotyped rituals that can serve as clocks¹². Such rituals can include orofacial movements and could easily go unnoticed while animals were maintaining fixations. Critically, this type of brief ritualistic movements has been previously shown to be drastically impaired by lesions of the sensorimotor region of striatum¹⁰. The presence of habit-like movements during interval presentation, controlled by distinct processes than full-body reward-oriented movements, could provide a unifying explanation to apparently contradictory interpretations on the striatal function in decision making and motor control. Indeed, striatal population dynamics may control a latent process that can bidirectionally control the speed of decision and execution of automatized actions, while average activity in the brain region would control the vigor of reward-oriented actions.

Of course, the above possibility might sound quite speculative but one should not underestimate the ability of animals to solve tasks in different ways than assumed by their human experimenters¹³. Thus, as any important study, the one of Monteiro et al. engenders new questions. It certainly demonstrates the importance and power of using subtle alterations of network dynamics to tackle functional questions in neuroscience. Reconciling the seemingly contradictory views on striatal function over the past years will require new experiments with different approaches, debates, and passionate disagreements; in other words, the normal and necessary business of science in the making¹⁴.

## References

1. Church, R. M. Properties of the Internal Clock. *Ann. N. Y. Acad. Sci.* **423**, 566–582 (1984).

2. Buhusi, C. V. & Meck, W. H. What makes us tick? Functional and neural mechanisms of interval timing. *Nat. Rev. Neurosci.* **6**, 755–765 (2005).

3. Paton, J. J. & Buonomano, D. V. The Neural Basis of Timing: Distributed Mechanisms for Diverse Functions. *Neuron* **98**, 687–705 (2018).
4. Monteiro, T. et al. Using temperature to analyse the neural basis of a time-based decision. 2020.08.24.251827 Preprint at https://doi.org/10.1101/2020.08.24.251827 (2022).

5. Gouvêa, T. S. et al. Striatal dynamics explain duration judgments. *eLife* **4**, e11386 (2015).

6. Long, M. A. & Fee, M. S. Using temperature to analyse temporal dynamics in the songbird motor pathway. *Nature* **456**, 189–194 (2008).

7. Banerjee, A., Egger, R. & Long, M. A. Using focal cooling to link neural dynamics and behavior. *Neuron* **109**, 2508–2518 (2021).

8. Robbe, D. & Dudman, J. T. *The Basal Ganglia invigorate actions and decisions*. (2020).

9. Banou, E. Kinesia paradoxa: a challenging Parkinson's phenomenon for simulation. *Adv. Exp. Med. Biol.* **822**, 165–177 (2015).

10. Dhawale, A. K., Wolff, S. B. E., Ko, R. & Ölveczky, B. P. The basal ganglia control the detailed kinematics of learned motor skills. *Nat. Neurosci.* **24**, 1256–1269 (2021).

11. Thura, D. & Cisek, P. The Basal Ganglia Do Not Select Reach Targets but Control the Urgency of Commitment. *Neuron* **95**, 1160-1170.e5 (2017).

12. Robbe, D. Lost in time: relocating the perception of duration outside the brain. (2021).

13. Despret, V. Thinking Like a Rat. *Angelaki* **20**, 121–134 (2015).

14. Latour, B. *Science in action: How to follow scientists and engineers through society.* (Harvard university press, 1987).

**Figure 1. Temperature manipulation biases time-based decisions.** A) Schematic representation of the binary time interval categorization task. B) Warming the dorsal striatum increased the distance traveled in neuronal space leading to categorizing near-boundary time intervals as long ones. C) Cooling the striatum led to opposite effects. D) In a space-time representation, population dynamics associated with striatal warming (cooling) appear contracted (dilated).
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